Hire the Best IBM DataPower Professionals

I am a tech-agnostic data engineer who enjoys solving complex data problems, finding patterns in messy datasets, and making sure the work actually supports the business. My focus is always on clean architecture, performance, and making data useful - not just moving it around.Here is what I have worked with: - Programming & Scripting: Python (Flask, FastAPI, Django, Selenium, PySpark), SQL - Data Engineering & Integration: Talend, Mage.ai, Apache Airflow, Airbyte, Databricks, Kafka, Debezium - Databases & Data Warehousing: Data Modeling, PostgreSQL, MySQL, Snowflake, Greenplum, MongoDB, Firebase, ClickHouse - Cloud & DevOps: AWS (Lambda, API Gateway, S3, RDS, SQS and more), Docker, Kubernetes, Azure DevOps, Terraform, CloudFormation - Security & Compliance: Secure and compliant pipeline design (HIPAA, GDPR, SOC 2), data governance, privacy-first architectures - Testing & Automation: Postman, Cypress.io, Swagger, Automated Data Workflows - Data Visualization: Power BI, Metabase, Google Data Studio, Grafana - Collaboration & Leadership: Cross-functional team mentoring, process optimization, data-driven decision-making

Messy data slowing your team down? I build scalable ETL/ELT pipelines and modern cloud architectures on Azure, Databricks, Fabric, and Snowflake that turn raw, chaotic data into clean, analytics-ready systems fast and reliably. I bridge the gap between fragmented data sources and production-grade dashboards, seamlessly adapting to your existing infrastructure rather than forcing an expensive rebuild. What I Can Help You With: Data Warehouse & Lakehouse Architecture: Implementing Medallion design patterns (Bronze → Silver → Gold) using Delta Lake, Microsoft Fabric OneLake, and Snowflake. Scalable ETL/ELT Ingestion: Building automated, metadata-driven pipelines via Azure Data Factory, Fabric Pipelines, Databricks (PySpark/SQL), and dbt. Real-Time Data Streaming: Architecting low-latency workflows using Apache Kafka, Azure Event Hubs, and streaming engines. Database Design & Optimization: Performance tuning, indexing, and data modeling for PostgreSQL, Azure SQL, and cloud warehouses. Proven Project Highlights: Microsoft Fabric Incremental Pipeline: Built a control-table pattern using Get Metadata, Lookup, and ForEach loops to orchestrate zero-duplicate, quarterly ingestion from SharePoint into OneLake via Dataflow Gen2. Azure/Databricks Streaming: Developed a restaurant analytics platform processing 80,000+ events/day, cutting reporting lag from 6 hours to under 3 minutes. Kafka/Snowflake Pipeline: Engineered a real-time stock market data pipeline tracking 120+ tickers with under 8 seconds end-to-end latency. I write clean, documented code your team can maintain long-term and provide transparent daily updates. Message me with your data challenge and I’ll walk you through exactly how to solve it.

💼 About Me I’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. I’m passionate about solving complex data problems , from extraction and transformation to analytics and visualization ,ensuring every dataset tells a meaningful story. -------------------- 🚀 What I Do -------------------- 🔹 Design, build, and maintain ETL pipelines using IBM DataStage for full and incremental data loads. 🔹 Integrate and transform data from PostgreSQL, SQL Server, APIs, and flat files. 🔹Develop data validation and quality checks to ensure accuracy and consistency. 🔹 Automate data workflows using Python (Pandas, NumPy, Requests, BeautifulSoup, Selenium). 🔹 Create interactive dashboards and business reports in Power BI. 🔹Perform data cleaning, analysis, and visualization for actionable insights. 🔹Build 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. ------------------------- 🧠 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 -------------------------- 📂 Notable Projects -------------------------- 🔹 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. 🔹Shopify Sales Data Automation: Developed Python-based scripts to clean, merge, and analyze sales data, then visualized KPIs in Power BI dashboards. 🔹E-commerce Web Scraping: Built Python scraping bots (BeautifulSoup + Selenium) to extract product and pricing data from multiple online sources. 🔹Data 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 — from collection to insight delivery while maintaining quality and performance at scale. ------------------------------- 🎯 What You Can Expect ------------------------------- 🔹 Scalable, well-documented, and optimized data solutions 🔹 Timely delivery with clear communication 🔹 High data accuracy and performance-focused results 🔹 A proactive, detail-oriented, and reliable collaboration If you’re looking for a reliable Data Engineer or Data Analyst who can design end-to-end pipelines, automate workflows, and deliver insightful analytics . let’s connect and discuss how I can bring value to your project. 🚀

𝗬𝗼𝘂𝗿 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗿𝘂𝗻𝘀 𝗼𝗻 𝗱𝗮𝘁𝗮 - 𝗯𝘂𝘁 𝗼𝗻𝗹𝘆 𝗶𝗳 𝘁𝗵𝗮𝘁 𝗱𝗮𝘁𝗮 𝗶𝘀 𝗮𝗰𝗰𝘂𝗿𝗮𝘁𝗲, 𝗮𝗰𝗰𝗲𝘀𝘀𝗶𝗯𝗹𝗲, 𝗮𝗻𝗱 𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗯𝗹𝗲. I help companies build scalable data platforms that eliminate manual reporting, automate complex workflows, and transform raw data into meaningful business insights. Whether you're starting from disconnected spreadsheets or modernizing an existing cloud infrastructure, I design data solutions that are reliable, efficient, and built to scale. With 4+ years of hands-on experience, I've developed enterprise-grade pipelines, implemented Medallion Architecture, optimized large-scale Spark workloads, automated data ingestion from multiple sources, and delivered analytics-ready datasets for healthcare, insurance, and enterprise organizations. 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲: ▶End-to-end ETL/ELT pipeline development ▶Azure Databricks & PySpark data engineering ▶Azure Data Factory & workflow automation ▶Data migration and cloud modernization ▶Data warehousing & Medallion Architecture ▶SQL optimization & performance tuning ▶Power BI dashboards & business intelligence ▶Data integration using APIs and cloud services ▶Data quality, governance & validation ▶BigQuery, Snowflake & Azure SQL solutions Every successful data project starts with understanding the business problem; not just the technology. Before writing a single line of code, I evaluate your existing architecture, identify bottlenecks, and design a solution that improves performance, reduces operational costs, and delivers trusted data for decision-making. 𝗜𝗳 𝘆𝗼𝘂 𝗻𝗲𝗲𝗱 𝗮 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝘄𝗵𝗼 𝗰𝗮𝗻 𝗯𝘂𝗶𝗹𝗱 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀, 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗰𝗹𝗼𝘂𝗱 𝗱𝗮𝘁𝗮 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀, 𝗮𝗻𝗱 𝘁𝘂𝗿𝗻 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝗱𝗮𝘁𝗮 𝗶𝗻𝘁𝗼 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝘃𝗮𝗹𝘂𝗲, 𝗹𝗲𝘁'𝘀 𝗱𝗶𝘀𝗰𝘂𝘀𝘀 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗷𝗲𝗰𝘁.

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. 🎯 Core Expertise: ✅ 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. ✅ 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. ✅ 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. ✅ 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. ✅ 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. ✅ Data Quality, Governance & Observability: Automated data quality frameworks, SLA monitoring, auditable lineage, data catalog and metadata management, and observability that catches bad data early. ✅ 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. ✅ AI-Ready Data Infrastructure: Pipelines engineered to feed LLMs and ML systems with clean, structured, high-quality data, from ingestion through transformation to serving. ------------------------------------------------------ ⚙️Tech Stack: ⚡ Warehouses & Lakehouse: Snowflake | BigQuery | Redshift | Databricks | Microsoft Fabric | Athena | Delta Lake | Iceberg ⚡ Transformation: dbt | SQLMesh | Spark | PySpark | AWS Glue | EMR | Star Schema | Medallion Architecture ⚡ Orchestration: Airflow (GCP Cloud Composer and AWS MWAA) | Dagster | Prefect | Azure Data Factory | Step Functions ⚡ Streaming: Kafka | Flink | Kinesis | Pub/Sub | Spark Structured Streaming | ClickHouse ⚡ Ingestion: Fivetran | Airbyte | Matillion | Stitch | Hevo | Meltano | CDC ⚡ Governance & Catalog: Glue Data Catalog | Lake Formation | Unity Catalog | Microsoft Purview | Dataplex ⚡ Cloud: AWS | GCP | Azure ⚡ Languages: Python | SQL (Snowflake, BigQuery, T-SQL, PL/pgSQL) | FastAPI ⚡ Databases: PostgreSQL | MySQL | SQL Server | DynamoDB | MongoDB ⚡ BI & Reporting: Looker | Tableau | Power BI | GA4 | Metabase | Superset | Streamlit | Grafana ------------------------------------------------------ ⭐ What Clients Say: 🏅 "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." – Anita, Head of Product, FinTech SaaS 🏅 "He designed a zero-downtime migration to a modern data warehouse that cut query latency by more than half while keeping our SLAs intact." – Daniel, VP of Data, AdTech Firm 🏅 "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." – Mark, Director of Data Engineering, E-commerce Startup 🏅 "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%." – Leo, Head of Analytics, HealthTech SaaS ------------------------------------------------------ 🏆 TOP RATED PLUS | EXPERT-VETTED | Top 1% on Upwork | 8+ Years Experience | 100% Job Success 🚀 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!

I build the data infrastructure behind confident business decisions. Clean pipelines, structured warehouses, automated workflows, and dashboards that actually mean something. I am a Data Engineer and BI Developer specializing in end-to-end data solutions across the Microsoft ecosystem. I design and deliver scalable data pipelines, cloud-based warehouses, and analytics-ready environments using Microsoft Fabric, Azure Data Factory, Azure Synapse, Databricks, SSIS, Python, and SQL, paired with executive-grade Power BI dashboards that turn raw data into real business visibility. My work sits at the intersection of data engineering and business intelligence. I don't just move data. I architect structured, maintainable environments that organizations can own, scale, and trust for long-term decision-making. What I Deliver - End-to-end data pipeline design and implementation using Azure Data Factory, Microsoft Fabric, and Databricks - Data warehouse architecture with clean, well-modeled schemas (star schema, dimensional modeling) built for performance and clarity - ETL/ELT development and automation including ingestion, transformation, scheduling, monitoring, and error handling across multiple source systems - Integration of diverse data sources including CRMs, ERPs, accounting platforms (QuickBooks, Xero), ecommerce systems (Shopify, Amazon), marketing APIs, CSV/Excel files, and cloud databases - Microsoft Fabric implementation including lakehouses, warehouses, pipelines, and paginated reports within the Fabric ecosystem - SQL development, query optimization, and stored procedure design for high-performance reporting - Python scripting for data automation, transformation, and API-based data extraction SSIS package development and maintenance for legacy and hybrid environments - Interactive Power BI dashboards and reports including KPI tracking, contribution margin analysis, profitability reporting, inventory analytics, and operational visibility - Documentation, SOPs, and structured handover materials so internal teams can confidently maintain and extend solutions independently Tools & Technologies - Microsoft Fabric - Azure Data Factory - Azure Synapse Analytics - Azure Data Lake Storage - Databricks - Python - SQL Server & SQL - SSIS - Power BI (Desktop, Service, Embedded, Paginated Reports) - Power Query & DAX - Microsoft Excel How I Work - Full ownership of delivery, from understanding your data landscape through to pipeline implementation, dashboard development, documentation, and team training - Focus on building solutions that are simple, well-structured, and designed for in-house sustainability, not black boxes that create dependency - Whether you need a greenfield data platform, an existing infrastructure restructured, or a reliable reporting layer connected to your operational systems, I bring the engineering discipline and BI expertise to deliver it cleanly and on time If you need a data engineer who can own the full journey from raw data to reliable reporting, let's connect. I'd love to understand your data challenges and build something that actually works.