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Paresh R.

Karachi, Pakistan

$20/hr
4.7
4 jobs

๐Ÿš€ Data Engineer & BI Developer | Microsoft Power BI & Fabric Certified Expert | Data Scraping & Web Automation Specialist | 6+ Years Experience ๐Ÿ’ก Looking to turn raw, messy, or manual data into automated pipelines and powerful dashboards that drive real business decisions? I specialize in Data Engineering, Microsoft Fabric, Power BI, and Python-based Web Scraping & Automation, helping companies: โœ”๏ธ Design and deliver high-impact Power BI dashboards & reports for executive decision-making โœ”๏ธ Build scalable ETL/ELT pipelines using Microsoft Fabric, Azure Data Factory & Azure Databricks โœ”๏ธ Automate manual data collection through Python web scraping & automation (Selenium, BeautifulSoup, APIs) โœ”๏ธ Migrate legacy BI platforms (Tableau, QlikView) to modern Power BI & Qlik Sense environments โœ”๏ธ Eliminate manual reporting delays with real-time, automated data pipelines ๐Ÿ† Microsoft Certified โ€” 4x Expert: โœ… Power BI Data Analyst Associate (PL-300) โœ… Fabric Analytics Engineer Associate โœ… Fabric Data Engineer Associate โœ… Qlik Data Analytics Certification ๐Ÿ“Š Why Work With Me? โœ… 6+ years of experience as a Data Engineer & BI Developer across banking, retail, pharma, manufacturing & energy โœ… Delivered 400+ dashboards and 200+ reports for global and enterprise clients โœ… Built 60+ ETL pipelines automating data workflows for international clients โœ… Created 100+ data scraping solutions and 50+ web automation systems using Python โœ… Migrated 30+ dashboards from Tableau to Power BI and 50+ from QlikView to Qlik Sense โœ… 100+ projects delivered on Freelancing Platform with 5-star ratings and 98% client retention โœ… Recently worked with: Harley-Davidson, HBL, Western Union, Pakistan State Oil (PSO), Engro Energy, Searle Pharmaceuticals, and IBEX Global ๐Ÿ”ฅ Recent Success Stories: โœ”๏ธ Cut ETL/dashboard refresh times from 4โ€“5 hours to 15 minutes by redesigning enterprise data pipelines at Pakistan State Oil โœ”๏ธ Eliminated 2โ€“3 days of manual reporting delays at IBL Group by deploying automated real-time pipelines with Qlik Replicate โœ”๏ธ Boosted transaction success rates by 15% and transaction values by 20% through pipeline and analytics optimization at HBL โœ”๏ธ Migrated 30+ enterprise dashboards from Tableau to Power BI, earning a Western Union excellence award Let's talk about how I can build your data infrastructure, automate your workflows, and turn your data into your most powerful business asset! ๐Ÿš€ My skills: Data Engineering, Microsoft Fabric (Lakehouse, Data Factory, Dataflows Gen2), Power BI (Dashboards, Reports, DAX, Power Query), Azure Data Factory, Azure Databricks, PySpark, Apache Spark, Python, SQL, Web Scraping (Selenium, BeautifulSoup), Web Automation, API Integration, ETL/ELT Pipeline Design, Data Modeling (Star & Snowflake Schema), Data Warehousing, Apache Airflow, Qlik Sense, Qlik Replicate, BigQuery, Snowflake, Data Validation, Workflow Automation

  • SQL
  • Dashboard
  • Python
  • Tableau
  • Data Visualization
  • Qlik Sense
  • Microsoft Power BI
  • Looker
  • Data Modeling
  • Data Warehousing & ETL Software
  • Snowflake
  • Data Scraping
  • Financial Reporting
  • Data Analysis Consultation
  • ETL Pipeline
  • Apache Airflow
  • NoSQL Database
Muhammad H.

Karachi, Pakistan

$10/hr
5.0
1 jobs

Slow pipelines, unreliable data, or a warehouse that breaks every time the source changes? I build data systems that don't. I'm a ๐— ๐—ถ๐—ฐ๐—ฟ๐—ผ๐˜€๐—ผ๐—ณ๐˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฒ๐—ฑ ๐—™๐—ฎ๐—ฏ๐—ฟ๐—ถ๐—ฐ ๐——๐—ฎ๐˜๐—ฎ ๐—˜๐—ป๐—ด๐—ถ๐—ป๐—ฒ๐—ฒ๐—ฟ with 5 years of experience delivering end-to-end data engineering and BI solutions. I currently work at Pakistan's largest payment gateway, a high volume fintech environment where ๐—ง๐—•-๐˜€๐—ฐ๐—ฎ๐—น๐—ฒ ๐˜๐—ฟ๐—ฎ๐—ป๐˜€๐—ฎ๐—ฐ๐˜๐—ถ๐—ผ๐—ป๐—ฎ๐—น ๐—ฑ๐—ฎ๐˜๐—ฎ, strict governance, and zero tolerance for pipeline failures are the daily reality. My specialty is building systems that are ๐—ฎ๐—ฟ๐—ฐ๐—ต๐—ถ๐˜๐—ฒ๐—ฐ๐˜๐—ฒ๐—ฑ ๐—ฝ๐—ฟ๐—ผ๐—ฝ๐—ฒ๐—ฟ๐—น๐˜† ๐—ณ๐—ฟ๐—ผ๐—บ ๐˜๐—ต๐—ฒ ๐˜€๐˜๐—ฎ๐—ฟ๐˜ metadata-driven, layered, monitored, and built to scale. ๐—ช๐—›๐—”๐—ง ๐—œ ๐—•๐—จ๐—œ๐—Ÿ๐—— โœฆ ๐— ๐—ฒ๐˜๐—ฎ๐—ฑ๐—ฎ๐˜๐—ฎ-๐——๐—ฟ๐—ถ๐˜ƒ๐—ฒ๐—ป ๐—˜๐—ง๐—Ÿ/๐—˜๐—Ÿ๐—ง ๐—ฃ๐—ถ๐—ฝ๐—ฒ๐—น๐—ถ๐—ป๐—ฒ๐˜€ Control logic lives in configuration, not hardcoded. One framework handles dozens of sources with built-in logging, error handling, and restartability. Proven: reduced ETL runtime by ๐Ÿฏ๐Ÿด% on a production enterprise warehouse by eliminating redundant mapping layers. โœฆ ๐—˜๐—ป๐˜๐—ฒ๐—ฟ๐—ฝ๐—ฟ๐—ถ๐˜€๐—ฒ ๐——๐—ฎ๐˜๐—ฎ ๐—ช๐—ฎ๐—ฟ๐—ฒ๐—ต๐—ผ๐˜‚๐˜€๐—ฒ ๐——๐—ฒ๐˜€๐—ถ๐—ด๐—ป End-to-end warehouse design across ๐—ฆ๐˜๐—ฎ๐—ด๐—ถ๐—ป๐—ด โ†’ ๐—–๐—ผ๐—ฟ๐—ฒ โ†’ ๐—š๐—ผ๐—น๐—ฑ (Medallion Architecture), with star/snowflake schema modeling, incremental loading, duplicate handling, and structured audit logging baked in. โœฆ ๐— ๐—ถ๐—ฐ๐—ฟ๐—ผ๐˜€๐—ผ๐—ณ๐˜ ๐—™๐—ฎ๐—ฏ๐—ฟ๐—ถ๐—ฐ ๐—ฆ๐—ผ๐—น๐˜‚๐˜๐—ถ๐—ผ๐—ป๐˜€ Lakehouse and Warehouse design on OneLake, Fabric Data Factory pipelines, semantic models with ๐—ฅ๐—ผ๐˜„-๐—Ÿ๐—ฒ๐˜ƒ๐—ฒ๐—น ๐—ฆ๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜† (๐—ฅ๐—Ÿ๐—ฆ), and report publishing as Fabric Apps for internal teams and external stakeholders. โœฆ ๐—”๐˜‡๐˜‚๐—ฟ๐—ฒ & ๐——๐—ฎ๐˜๐—ฎ๐—ฏ๐—ฟ๐—ถ๐—ฐ๐—ธ๐˜€ ๐—ฃ๐—ถ๐—ฝ๐—ฒ๐—น๐—ถ๐—ป๐—ฒ๐˜€ ADF orchestrated cloud pipelines and PySpark based distributed data processing on Databricks for large-scale, partitioned datasets. โœฆ ๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—•๐—œ & ๐—ฆ๐—ฆ๐—ฅ๐—ฆ ๐—ฅ๐—ฒ๐—ฝ๐—ผ๐—ฟ๐˜๐—ถ๐—ป๐—ด Semantic model design, DAX measures, drill-through dashboards, RLS enforcement, SSRS and Report Builder reports, and Fabric App deployment for enterprise stakeholders. โœฆ ๐—Ÿ๐—ฒ๐—ด๐—ฎ๐—ฐ๐˜† ๐— ๐—œ๐—ฆ ๐— ๐—ถ๐—ด๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป Migrated 20+ reports from legacy systems into a centralized, modern BI architecture without disrupting ongoing operations. ๐—ฅ๐—˜๐—–๐—˜๐—ก๐—ง ๐—ฅ๐—˜๐—ฆ๐—จ๐—Ÿ๐—ง๐—ฆ โ€ข Reduced ETL runtime by ๐Ÿฏ๐Ÿด% (4 hrs โ†’ 2.5 hrs) by optimizing metadata-driven SSIS pipelines โ€ข Built automated SFTP ingestion pipelines with archive logic to ensure ๐—ถ๐—ป๐—ฐ๐—ฟ๐—ฒ๐—บ๐—ฒ๐—ป๐˜๐—ฎ๐—น, ๐—ฑ๐˜‚๐—ฝ๐—น๐—ถ๐—ฐ๐—ฎ๐˜๐—ฒ-๐—ณ๐—ฟ๐—ฒ๐—ฒ data loading โ€ข Delivered ๐—บ๐˜‚๐—น๐˜๐—ถ๐—ฝ๐—น๐—ฒ ๐—˜๐—ป๐˜๐—ฒ๐—ฟ๐—ฝ๐—ฟ๐—ถ๐˜€๐—ฒ ๐——๐—ฎ๐˜๐—ฎ ๐—ช๐—ฎ๐—ฟ๐—ฒ๐—ต๐—ผ๐˜‚๐˜€๐—ฒ๐˜€ supporting different business products across fintech, billing, and payments โ€ข Published ๐Ÿญ๐Ÿฑ+ ๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—•๐—œ ๐—ฟ๐—ฒ๐—ฝ๐—ผ๐—ฟ๐˜๐˜€ as Fabric Apps with Row Level Security for external stakeholders โ€ข Onboarded 10+ new source tables into a redesigned data warehouse while improving ETL performance and storage efficiency โ€ข Worked extensively with ๐—ง๐—•-๐˜€๐—ฐ๐—ฎ๐—น๐—ฒ ๐˜๐—ฟ๐—ฎ๐—ป๐˜€๐—ฎ๐—ฐ๐˜๐—ถ๐—ผ๐—ป๐—ฎ๐—น ๐—ฑ๐—ฎ๐˜๐—ฎ in a high-volume payment processing environment. ๐—–๐—ข๐—ฅ๐—˜ ๐—ฆ๐—ง๐—”๐—–๐—ž ๐— ๐—ถ๐—ฐ๐—ฟ๐—ผ๐˜€๐—ผ๐—ณ๐˜ ๐—™๐—ฎ๐—ฏ๐—ฟ๐—ถ๐—ฐ | ๐—”๐˜‡๐˜‚๐—ฟ๐—ฒ ๐——๐—ฎ๐˜๐—ฎ ๐—™๐—ฎ๐—ฐ๐˜๐—ผ๐—ฟ๐˜† | ๐—”๐˜‡๐˜‚๐—ฟ๐—ฒ ๐——๐—ฎ๐˜๐—ฎ๐—ฏ๐—ฟ๐—ถ๐—ฐ๐—ธ๐˜€ | ๐—ฃ๐˜†๐—ฆ๐—ฝ๐—ฎ๐—ฟ๐—ธ | ๐—”๐—ฝ๐—ฎ๐—ฐ๐—ต๐—ฒ ๐—ฆ๐—ฝ๐—ฎ๐—ฟ๐—ธ | ๐—ฆ๐—ฆ๐—œ๐—ฆ | ๐—ฆ๐—ค๐—Ÿ ๐—ฆ๐—ฒ๐—ฟ๐˜ƒ๐—ฒ๐—ฟ | ๐—ข๐—ฟ๐—ฎ๐—ฐ๐—น๐—ฒ | ๐—ฃ๐—ผ๐˜€๐˜๐—ด๐—ฟ๐—ฒ๐—ฆ๐—ค๐—Ÿ | ๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—•๐—œ | ๐—ฆ๐—ฆ๐—ฅ๐—ฆ | ๐—ง-๐—ฆ๐—ค๐—Ÿ | ๐—ฃ๐—Ÿ/๐—ฆ๐—ค๐—Ÿ | ๐——๐—ฎ๐˜๐—ฎ ๐—ช๐—ฎ๐—ฟ๐—ฒ๐—ต๐—ผ๐˜‚๐˜€๐—ถ๐—ป๐—ด | ๐— ๐—ฒ๐—ฑ๐—ฎ๐—น๐—น๐—ถ๐—ผ๐—ป ๐—”๐—ฟ๐—ฐ๐—ต๐—ถ๐˜๐—ฒ๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ | ๐—ฆ๐˜๐—ฎ๐—ฟ ๐—ฆ๐—ฐ๐—ต๐—ฒ๐—บ๐—ฎ | ๐—ฆ๐—ป๐—ผ๐˜„๐—ณ๐—น๐—ฎ๐—ธ๐—ฒ ๐—ฆ๐—ฐ๐—ต๐—ฒ๐—บ๐—ฎ | ๐—˜๐—ง๐—Ÿ/๐—˜๐—Ÿ๐—ง | ๐—Ÿ๐—ฎ๐—ธ๐—ฒ๐—ต๐—ผ๐˜‚๐˜€๐—ฒ ๐—•๐—˜๐—ฆ๐—ง-๐—™๐—œ๐—ง ๐—ฃ๐—ฅ๐—ข๐—๐—˜๐—–๐—ง๐—ฆ โ€ข Data warehouse or lakehouse design from scratch โ€ข ETL/ELT pipeline build, optimization, or troubleshooting โ€ข Microsoft Fabric or Azure migration from legacy on-prem systems โ€ข Power BI, SSRS, or Fabric App reporting solutions โ€ข SQL performance tuning, stored procedures, and indexing โ€ข Production pipeline monitoring, job scheduling, and failure resolution ๐—›๐—ข๐—ช ๐—œ ๐—ช๐—ข๐—ฅ๐—ž I understand your business process, data sources, and reporting needs first. Then I design a practical architecture, build clean and observable pipelines, validate the data, and deliver reporting ready models your team can actually trust with ๐—น๐—ผ๐—ด๐—ด๐—ถ๐—ป๐—ด, ๐—ฒ๐—ฟ๐—ฟ๐—ผ๐—ฟ ๐—ต๐—ฎ๐—ป๐—ฑ๐—น๐—ถ๐—ป๐—ด, and ๐—ท๐—ผ๐—ฏ ๐˜€๐—ฐ๐—ต๐—ฒ๐—ฑ๐˜‚๐—น๐—ถ๐—ป๐—ด built in from day one, not added as an afterthought. ๐Ÿ“ฉ ๐—ฆ๐—ฒ๐—ป๐—ฑ ๐—บ๐—ฒ ๐—ฎ ๐—บ๐—ฒ๐˜€๐˜€๐—ฎ๐—ด๐—ฒ ๐˜„๐—ถ๐˜๐—ต ๐˜†๐—ผ๐˜‚๐—ฟ ๐—ฝ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜ ๐—ฑ๐—ฒ๐˜๐—ฎ๐—ถ๐—น๐˜€. ๐—œ ๐—ฟ๐—ฒ๐˜€๐—ฝ๐—ผ๐—ป๐—ฑ ๐—พ๐˜‚๐—ถ๐—ฐ๐—ธ๐—น๐˜† ๐—ฎ๐—ป๐—ฑ ๐˜„๐—ถ๐—น๐—น ๐—ผ๐˜‚๐˜๐—น๐—ถ๐—ป๐—ฒ ๐—ฎ ๐—ฐ๐—น๐—ฒ๐—ฎ๐—ฟ ๐—ฎ๐—ฝ๐—ฝ๐—ฟ๐—ผ๐—ฎ๐—ฐ๐—ต ๐—ณ๐—ผ๐—ฟ ๐˜†๐—ผ๐˜‚๐—ฟ ๐—ฝ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜.

  • Data Engineering
  • ETL Pipeline
  • Microsoft Azure
  • Microsoft Power BI
  • Databricks Platform
  • Data Warehousing
  • Data Lake
  • SQL
  • Data Modeling
  • SQL Server Integration Services
  • SQL Server Reporting Services
  • Microsoft SQL Server
  • Oracle
  • Fabric
  • Database Development
  • PySpark
  • Business Intelligence
  • PostgreSQL
  • Microsoft Power BI Data Visualization
  • Big Data
Waheed M.

Rawalpindi, Pakistan

$30/hr
4.8
361 jobs

Looking for an Azure Data Engineer to build scalable ETL pipelines, modernize your Azure SQL database, or implement Microsoft Fabric / Databricks analytics? With over 6,000+ hours logged, $200K+ earned, and a 100% Job Success Rate, I help businesses transform messy raw data into reliable cloud data platforms and automated Power BI dashboards. Whether you need an end-to-end cloud migration, delta lake architecture, or query performance tuning, I deliver clean, production-ready solutions designed for long-term growth. Core Services & Capabilities: โœ” Microsoft Fabric & Azure Data Factory: Automated ETL/ELT pipeline design & ingestion โœ” Data Warehousing & Architecture: Azure SQL, Synapse Analytics, Medallion Architecture (Delta Lake) โœ” Advanced Analytics & Python: Data transformation, PySpark, API integrations, web scraping โœ” Business Intelligence: Executive Power BI dashboards, DirectQuery optimization, Looker Studio โœ” Database Migration & Optimization: Legacy SQL Server to Azure, PostgreSQL, T-SQL performance tuning Technologies I Work With Daily: โ€ข Cloud & Big Data: Azure Data Factory (ADF), Microsoft Fabric, Databricks, Azure Synapse, Delta Lake โ€ข Databases: Azure SQL, MS SQL Server, PostgreSQL, AWS BigQuery โ€ข Languages & Automation: Python, PySpark, T-SQL, PL/pgSQL โ€ข Analytics & BI: Power BI, Looker Studio, SSIS - fawn mast wolf Letโ€™s turn your complex data challenges into an automated, high-performance solution. Send me an invite or message, and let's discuss your project goals!

  • Data Engineering
  • Data Warehousing & ETL Software
  • Microsoft Azure SQL Database
  • Microsoft SQL Server
  • Database
  • Data Warehousing
  • ETL
  • ETL Pipeline
  • Data Ingestion
  • Data Migration
  • Python
  • SQL
  • Microsoft Power BI
  • Microsoft Power BI Data Visualization
  • Data Modeling
  • Microsoft Azure
  • Looker Studio
Adarsh R.

Bengaluru, India

$70/hr
5.0
38 jobs

I'm a Senior Data Engineer with 8+ years of strong technical expertise in building reliable and scalable data infrastructure, from data ingestion to transformation to warehousing, streaming, and data analytics, specializing in dbt, Snowflake, Airflow, Databricks (and more) across AWS, Azure, and GCP, with robust ELT and ETL pipelines. If your data pipelines are brittle, your data warehouse is slow, or your data was never built to scale, that is exactly what I fix, with fault tolerance, observability, and audit-ready quality engineered in from day one. I cover the full data engineering lifecycle: batch and real-time data pipelines, Modern Data Stack builds, lakehouse architecture, cloud and warehouse data migration, governance, and the data foundations that feed modern systems. ๐ŸŽฏ Core Expertise: โœ… Data Pipelines & Orchestration: End-to-end batch and real-time pipelines with Apache Airflow, Dagster, Prefect, AWS Step Functions, and Azure Data Factory. Idempotent, schema-drift tolerant, and monitored so failures surface before they reach your stakeholders. โœ… Cloud Warehousing & Lakehouse: Snowflake, BigQuery, Amazon Redshift, Databricks, and Microsoft Fabric, with Delta Lake and Apache Iceberg lakehouse foundations governed through the Glue Data Catalog and Lake Formation, with Athena and Redshift Spectrum for serverless queries, Medallion Architecture, partitioning, and performance tuning. โœ… Data Transformation & Modeling: dbt (Core and Cloud), SQLMesh, Spark and PySpark on EMR and AWS Glue, Star Schema and dimensional modeling, analytics engineering best practices, full test coverage, and CI/CD for data models. โœ… Streaming & Real-Time Analytics: Distributed streaming with Apache Kafka, Flink, Spark Structured Streaming, Kinesis, and Pub/Sub, including exactly-once semantics, dead-letter queues, CDC, and end-to-end latency guarantees. โœ… Data Ingestion & Integration: Fivetran, Airbyte, Matillion, Stitch, Hevo, Meltano, and custom CDC pipelines for near-real-time sync across structured, semi-structured, and unstructured sources. โœ… Data Quality, Governance & Observability: Automated data quality frameworks, SLA monitoring, auditable lineage, data catalog and metadata management, and observability that catches bad data early. โœ… Cloud Migration & Modernization: Zero-downtime migration handled end to end, from legacy warehouse assessment through cutover, with zero data loss and minimal downtime, replacing brittle ETL and ELT with a clean Modern Data Stack. โœ… AI-Ready Data Infrastructure: Pipelines engineered to feed LLMs and ML systems with clean, structured, high-quality data, from ingestion through transformation to serving. ------------------------------------------------------ โš™๏ธTech Stack: โšก Warehouses & Lakehouse: Snowflake | BigQuery | Redshift | Databricks | Microsoft Fabric | Athena | Delta Lake | Iceberg โšก Transformation: dbt | SQLMesh | Spark | PySpark | AWS Glue | EMR | Star Schema | Medallion Architecture โšก Orchestration: Airflow (GCP Cloud Composer and AWS MWAA) | Dagster | Prefect | Azure Data Factory | Step Functions โšก Streaming: Kafka | Flink | Kinesis | Pub/Sub | Spark Structured Streaming | ClickHouse โšก Ingestion: Fivetran | Airbyte | Matillion | Stitch | Hevo | Meltano | CDC โšก Governance & Catalog: Glue Data Catalog | Lake Formation | Unity Catalog | Microsoft Purview | Dataplex โšก Cloud: AWS | GCP | Azure โšก Languages: Python | SQL (Snowflake, BigQuery, T-SQL, PL/pgSQL) | FastAPI โšก Databases: PostgreSQL | MySQL | SQL Server | DynamoDB | MongoDB โšก BI & Reporting: Looker | Tableau | Power BI | GA4 | Metabase | Superset | Streamlit | Grafana ------------------------------------------------------ โญ What Clients Say: ๐Ÿ… "Adarsh rebuilt our analytics pipeline on Snowflake, Airflow, and dbt, giving us reliable, version-ready data. Reporting accuracy improved overnight, and we can finally trust the numbers." โ€“ Anita, Head of Product, FinTech SaaS ๐Ÿ… "He designed a zero-downtime migration to a modern data warehouse that cut query latency by more than half while keeping our SLAs intact." โ€“ Daniel, VP of Data, AdTech Firm ๐Ÿ… "Clean architecture, solid dbt models, and Airflow pipelines running without issues for months. He brought a level of engineering discipline we hadn't seen from a data consultant before." โ€“ Mark, Director of Data Engineering, E-commerce Startup ๐Ÿ… "We came to him with a Spark pipeline costing us a fortune and delivering stale data. He restructured the workflow logic and cut processing time by 70%." โ€“ Leo, Head of Analytics, HealthTech SaaS ------------------------------------------------------ ๐Ÿ† TOP RATED PLUS | EXPERT-VETTED | Top 1% on Upwork | 8+ Years Experience | 100% Job Success ๐Ÿš€ Ready to build a scalable, production-ready data infrastructure to turn your raw data into reliable, actionable business insights? Click the 'Invite to Job' button on the top right, and let's discuss your data pipeline!

  • Data Engineering
  • Snowflake
  • dbt
  • Apache Airflow
  • Python
  • SQL
  • Amazon Web Services
  • Google Cloud Platform
  • Microsoft Azure
  • Databricks Platform
  • PostgreSQL
  • ETL Pipeline
  • Data Warehousing
  • API Integration
  • Apache Kafka
  • PySpark
  • BigQuery
  • Data Modeling
  • Data Extraction
  • Big Data
Abdul H.

Lahore, Pakistan

$10/hr
5.0
4 jobs

๐Ÿ’ผ About Me Iโ€™m a Data Engineer & Data Analyst with 4 years of professional experience in designing scalable data pipelines, automating ETL workflows, and delivering data-driven business insights. My core expertise includes Python, SQL, Power BI, IBM DataStage, and Web Scraping, helping organizations turn raw data into actionable intelligence. Iโ€™m passionate about solving complex data problems , from extraction and transformation to analytics and visualization ,ensuring every dataset tells a meaningful story. -------------------- ๐Ÿš€ What I Do -------------------- ๐Ÿ”น Design, build, and maintain ETL pipelines using IBM DataStage for full and incremental data loads. ๐Ÿ”น Integrate and transform data from PostgreSQL, SQL Server, APIs, and flat files. ๐Ÿ”นDevelop data validation and quality checks to ensure accuracy and consistency. ๐Ÿ”น Automate data workflows using Python (Pandas, NumPy, Requests, BeautifulSoup, Selenium). ๐Ÿ”น Create interactive dashboards and business reports in Power BI. ๐Ÿ”นPerform data cleaning, analysis, and visualization for actionable insights. ๐Ÿ”นBuild custom web scraping solutions for data collection and trend analysis. I focus on reliability, scalability, and automation ,making sure your data systems perform efficiently and consistently over time. ------------------------- ๐Ÿง  Technical Skills ------------------------- Languages: Python, SQL ETL Tools: IBM DataStage, SSIS, AWS, Azure Databases: PostgreSQL, SQL Server, MySQL Visualization: Power BI, Excel Dashboards Automation & Analytics: Pandas, NumPy, PySpark, APIs Web Scraping: BeautifulSoup, Selenium, Requests Version Control: Git, GitHub -------------------------- ๐Ÿ“‚ Notable Projects -------------------------- ๐Ÿ”น Microfinance Bank Data Pipeline: Designed and implemented a complete ETL process using IBM DataStage, integrating client, loan, and transaction data into a centralized SQL Server database. ๐Ÿ”นShopify Sales Data Automation: Developed Python-based scripts to clean, merge, and analyze sales data, then visualized KPIs in Power BI dashboards. ๐Ÿ”นE-commerce Web Scraping: Built Python scraping bots (BeautifulSoup + Selenium) to extract product and pricing data from multiple online sources. ๐Ÿ”นData Quality & Validation Framework: Created automated SQL and DataStage-based validation scripts to ensure consistent and accurate ETL data processing. These projects strengthened my ability to manage end-to-end data processes โ€” from collection to insight delivery while maintaining quality and performance at scale. ------------------------------- ๐ŸŽฏ What You Can Expect ------------------------------- ๐Ÿ”น Scalable, well-documented, and optimized data solutions ๐Ÿ”น Timely delivery with clear communication ๐Ÿ”น High data accuracy and performance-focused results ๐Ÿ”น A proactive, detail-oriented, and reliable collaboration If youโ€™re looking for a reliable Data Engineer or Data Analyst who can design end-to-end pipelines, automate workflows, and deliver insightful analytics . letโ€™s connect and discuss how I can bring value to your project. ๐Ÿš€

  • Python
  • SQL
  • ETL Pipeline
  • ETL
  • Automation
  • Data Visualization
  • API
  • Microsoft Power BI
  • Database
  • Apache Airflow
  • PySpark
  • Microsoft Azure
  • dbt
  • Snowflake
  • Hive
  • Zapier
  • Automation Anywhere
  • n8n
Faisal S.

Rahim Yar Khan, Pakistan

$25/hr
5.0
16 jobs

๐ƒ๐š๐ญ๐š ๐„๐ง๐ ๐ข๐ง๐ž๐ž๐ซ๐ข๐ง๐  | ๐€๐–๐’ | ๐„๐“๐‹ ๐๐ข๐ฉ๐ž๐ฅ๐ข๐ง๐ž๐ฌ | ๐ƒ๐š๐ญ๐š ๐–๐š๐ซ๐ž๐ก๐จ๐ฎ๐ฌ๐ž | ๐€๐ˆ ๐€๐ฎ๐ญ๐จ๐ฆ๐š๐ญ๐ข๐จ๐ง | ๐‹๐‹๐Œ | ๐‘๐€๐† | ๐‚๐ก๐š๐ญ๐›๐จ๐ญ๐ฌ | ๐ง๐Ÿ–๐ง | ๐Ž๐ฉ๐ž๐ง๐€๐ˆ | ๐๐ฒ๐ญ๐ก๐จ๐ง I help businesses build scalable data pipelines and AI-powered systems that improve decision-making, reduce costs, and automate workflows. With 6+ years of experience as a Data Engineer and growing expertise in Generative AI, I design cloud-native data architectures and enhance them with AI-driven automation, insights, and intelligent workflows. Whether you're building from scratch, scaling your data systems, or looking to integrate AI into your operations, I deliver production-ready solutions that actually drive results. โญ ๐‚๐จ๐ฆ๐ฉ๐š๐ง๐ข๐ž๐ฌ ๐ˆ'๐ฏ๐ž ๐–๐จ๐ซ๐ค๐ž๐ ๐–๐ข๐ญ๐ก: ๐Ÿ”นFintech Startup processing millions of transactions/month across the U.S. ๐Ÿ”นGlobal B2B SaaS Platform with data operations across 20+ countries ๐Ÿ”นEU Healthcare Analytics Provider working with sensitive PHI data ๐Ÿ”นManufacturing Firm automating cross-platform data flows for ERP & MES ๐Ÿ”นMultiple Fortune-level enterprises through agency partnerships โญ ๐–๐ก๐š๐ญ ๐ˆ ๐๐ซ๐ข๐ง๐  ๐ญ๐จ ๐˜๐จ๐ฎ๐ซ ๐ƒ๐š๐ญ๐š ๐„๐ง๐ ๐ข๐ง๐ž๐ž๐ซ๐ข๐ง๐  ๐๐ซ๐จ๐ฃ๐ž๐œ๐ญ: โ€ข ETL/ELT Expertise: Airflow, AWS Glue, SSIS, custom orchestration, Apache Hadoop โ€ข Data Warehousing: Snowflake, Redshift, BigQuery, SQL Server, PostgreSQL โ€ข AWS Proficiency: Lambda, Step Functions, RDS, DynamoDB, S3, CloudFormation, Terraform โ€ขProgramming: Python (pandas, boto3), SQL, Shell scripting โ€ข Automation & Integration: API ingestion, serverless workflows, CI/CD pipelines โ€ข BI & Analytics: Power BI, Tableau, QuickSight, Looker โ€ข Best Practices: Version control, unit testing, GitOps, Dockerized environments โ€ข Security & Compliance: Handling of PII/PHI, audit-ready pipelines โญ๐†๐ž๐ง๐ž๐ซ๐š๐ญ๐ข๐ฏ๐ž ๐€๐ˆ ๐—ง๐—ฒ๐—ฐ๐—ต ๐—ฆ๐˜๐—ฎ๐—ฐ๐—ธ & ๐—ฆ๐—ธ๐—ถ๐—น๐—น๐˜€: โ€ข Languages & Frameworks: Python, Django, FastAPI, React,Next, Streamlit โ€ข AI/LLM Tools: OpenAI API, LangChain, Langgraph, MCP, Anthropic, ElevenLabs, Whisper โ€ข Automation & Infra: RAG pipelines, multi-agent frameworks, workflow orchestration, AWS, Azure โ€ข Integrations: CRMs, ERPs, Firebase, Slack, MS Teams, custom APIs โ€ข ML&DL (Tensoflow,PyTorch) โ€ข NLP โ€ข Large Language Models (LLMs) โ€ข Prompt Engineering โ€ข GANs โ€ข QueryGeneration (GenQ) โ€ข GPL for semantic search โ€ข LangChain โญ ๐–๐ก๐ฒ ๐–๐จ๐ซ๐ค ๐–๐ข๐ญ๐ก ๐Œ๐ž? ๐Ÿ”นClient-Focused Delivery: I prioritize measurable impact and long-term value ๐Ÿ”นClear Communication: Frequent updates, transparent planning, and no surprises ๐Ÿ”นTrusted Partner: Many clients return for new projects or refer others ๐—”๐—ฏ๐—ผ๐˜‚๐˜ ๐—บ๐˜† ๐—ฐ๐—ผ๐—บ๐—ฝ๐—ฎ๐—ป๐˜†: DotLabs is an Data engineering & AI-first development company specializing in Generative AI, automation, and domain-specific AI applications. With expertise in Python, JavaScript, AI frameworks, and cloud deployment, we deliver end-to-end, production-ready web and mobile solutions that turn AI innovation into real business impact. Letโ€™s build a system that not only handles your data, but uses AI to make it smarter. Send me a message and letโ€™s discuss your project. Data Engineering, AWS, ETL Pipelines, AI Automation, LLM, RAG, Chatbots #AIOperations #ProcessAutomation #AIWorkflow #DataAnalysis #WorkflowAutomation

  • Data Engineering
  • Data Analytics
  • Microsoft Power BI Data Visualization
  • Python
  • PostgreSQL
  • Data Warehousing & ETL Software
  • ETL Pipeline
  • AWS Development
  • Data Extraction
  • Microsoft Excel
  • Microsoft Azure
  • Microsoft Power BI Development
  • Looker Studio
  • Automation
  • AI Agent Development
  • Apache Hadoop
  • SaaS

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What does an IBM DataPower freelancer do?

An IBM DataPower freelancer configures and maintains IBM DataPower Gateway appliances to secure API traffic and manage message integration. This specialist builds processing rules that enforce access control and encryption standards across enterprise networks. They automate the deployment of these security policies using specialized configuration management tools to ensure consistent application across multiple devices. Their work focuses on keeping gateway services operational while protecting sensitive data from unauthorized access.

  • Configure DataPower Gateway services by creating specific objects such as handlers, mediation settings, and service definitions. The freelancer uses the REST management interface or SOAP Configuration Management interface to define how messages flow through the system. They set up multi-protocol gateways to handle various data formats and ensure proper routing between internal systems and external partners.
  • Implement security policies by writing processing rules that validate incoming requests and enforce TLS crypto settings. This work involves defining access control lists and certificate management protocols within the appliance configuration. The freelancer tests these rules to confirm they block malicious traffic while allowing legitimate business transactions to proceed without interruption.
  • Automate configuration builds and deployments using DataPower Configuration Manager and Ant-based command line tools. Instead of manual updates, the freelancer creates scripts that package configuration changes and promote them to target environments. This approach reduces human error during updates and ensures that development, testing, and production environments remain synchronized with approved security settings.
  • Perform operational maintenance by planning firmware upgrades and executing secure backup and restore procedures. The freelancer generates backup images of the appliance state and validates restore processes to support disaster recovery efforts. They monitor gateway performance through management interfaces to identify bottlenecks or failures in real time and adjust configurations to maintain service availability.

How to hire an IBM DataPower freelancer on Upwork

Step 1: Post a job

Define your integration and security requirements clearly to attract qualified specialists. Use the Job Post Generator powered by Umaโ„ข, Upwork's Mindful AI to draft a precise description in seconds. Describe your needs in a few sentences, and Uma creates a tailored post for this role. You can write a new post, update a saved draft, or reuse an existing post.

  • Specify whether you need configuration of DataPower Gateway services, implementation of TLS/crypto settings, or automation using DataPower Configuration Manager.
  • List required tools such as the REST management interface, SOMA interface, or Ant-based DCM tooling to filter for relevant technical experience.
  • Clarify if the work involves operational maintenance tasks like firmware upgrade planning or secure backup and restore validation for disaster recovery.

Step 2: Evaluate candidates

Look for portfolios that demonstrate hands-on experience with DataPower configuration objects and policy enforcement. Uma can run instant video interviews and build shortlists with side-by-side comparisons to speed up your review process.

  • Verify experience in creating processing rules and actions that implement specific security policies within the DataPower execution environment.
  • Check for evidence of automated deployment workflows using DCM scripts or UrbanCode Deploy plugins rather than manual configuration changes.
  • Confirm familiarity with secure backup and restore commands to ensure they can manage disaster recovery procedures correctly.

Step 3: Interview your top choices

Discuss specific technical scenarios to gauge their problem-solving approach and depth of knowledge. Schedule and conduct interviews within Upwork Messages, which generates an immediate transcript and summary after each session.

  • Ask how they handle version control and promotion of configuration objects across development, test, and production environments.
  • Request examples of complex mediation policies they have authored and how they tested these rules before deployment.
  • Inquire about their method for monitoring gateway services and troubleshooting performance issues using management interfaces.

Step 4: Agree on scope and begin work

Set clear milestones for configuration delivery and policy implementation to track progress effectively. Use Upwork Messages and the contract workroom for all communication and project management needs.

  • Define deliverables such as exported configuration packages, DCM build artifacts, or documented runbooks for secure restore operations.
  • Enable hourly tracking or set fixed-price milestones with project funds to secure payment for completed work stages.
  • Rely on identity verification and Hourly Payment Protection to maintain security and trust throughout the engagement.

Upwork is not affiliated with and does not sponsor or endorse any of the tools or services discussed in this article. These tools and services are provided only as potential options, and each reader and company should take the time needed to adequately analyze and determine the tools or services that would best fit their specific needs and situation.

The rates and information provided in this article are based on current data and industry sources available at the time of publication. Freelance rates can vary depending on factors such as experience, location, project scope, and market conditions. Readers are encouraged to conduct their own research to confirm current rates and trends, as this information may change over time.

How much does hiring an IBM DataPower freelancer cost?

Hiring an IBM DataPower freelancer typically costs $500-$2,500 per project, depending on scope and experience. Final pricing depends on technical complexity, required integrations, security policy depth, and the freelancer's experience level.

Configuration audit

$500-$1,000/project

Entry-level to mid-level
  • Identified gaps in current gateway settings
  • Prioritized steps to fix security issues
  • Updated notes on configuration state

Policy implementation

$1,000-$2,500/project

Mid-level
  • Configured access control and TLS settings
  • Validation logs for new security policies
  • Steps to apply rules to production

Automated deployment setup

$2,500-$4,500/project

Mid-level to senior-level
  • Ant-based commands for build automation
  • UrbanCode Deploy plugin settings
  • Instructions for automated promotion workflows

Disaster recovery planning

$4,500-$7,000/project

Senior-level
  • Secure backup image of appliance config
  • Validated steps for secure-restore process
  • Proof of successful restoration to compatible appliance

Full gateway integration

$7,000-$12,000/project

Expert-level
  • Deployed gateway handlers and mediation settings
  • End-to-end policy enforcement across APIs
  • Complete guide for monitoring and maintenance

Frequently asked questions

Is hiring an IBM DataPower freelancer worth it?

For most businesses, yes: hiring an IBM DataPower freelancer is worthwhile. These specialists configure secure API gateways and manage complex integration policies that require specific platform knowledge. You gain access to experts who automate deployments and handle firmware upgrades without retaining a full-time employee.

How do I evaluate IBM DataPower freelancer candidates?

Look for candidates who describe specific experience with DataPower Configuration Manager (DCM) and secure backup workflows. Ask them to explain how they use Ant-based commands to automate configuration promotions between environments. A strong candidate will detail their process for validating restore images during disaster recovery testing.

What tools does an IBM DataPower freelancer use?

An IBM DataPower freelancer uses the REST management interface and SOAP Configuration Management (SOMA) interface to modify device settings. They also employ DataPower Configuration Manager (DCM) for automated builds and secure-restore commands for disaster recovery.

What deliverables should I expect from an IBM DataPower freelancer?

You should receive deployed gateway service objects, processing rules, and security policy implementations. The freelancer also submits automated deployment scripts and documentation that describes how they managed the configuration state.