Business Intelligence and Data Analyst with a strong focus on data analysis, predictive analytics, and visualization tools. Proficient in SQL and Python, with extensive experience in building dashboards and delivering actionable insights across various sectors, including healthcare and retail.
Data Visualization
Google Sheets
Tableau
SQL
Microsoft Excel
Python
Matplotlib
Microsoft Power BI
RStudio
Data Analysis
Data Cleaning
BigQuery
Data Chart
pandas
Fabric
Hasini S.
Galle, Sri Lanka
$15/hr
5.0
2 jobs
I am an experienced Data Analyst who excelled in statistics, data analysis, and computer science. Currently, I am working as a Analytics Engineer at a sports manufacturing company. Moreover, I am a graduate of BSc(Hons.) in Physical Science at University of Colombo. I have the capacity to work with Power BI, Tableau, Quick Sight, Python, Snowflake, SQL, and PL SQL. Currently I am engaging with the Microsoft Fabric.
Data Analysis
Microsoft Power BI
Microsoft PowerApps
Tableau
SQL
Oracle PLSQL
Snowflake
Amazon QuickSight
Power Query
Microsoft Azure SQL Database
Python
R
Machine Learning
Data Science
Microsoft Power Automate
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 ๐ถ๐ฐ๐ฟ๐ผ๐๐ผ๐ณ๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฒ๐ฑ ๐๐ฎ๐ฏ๐ฟ๐ถ๐ฐ ๐๐ฎ๐๐ฎ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ 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 ๐ง๐-๐๐ฐ๐ฎ๐น๐ฒ ๐๐ฟ๐ฎ๐ป๐๐ฎ๐ฐ๐๐ถ๐ผ๐ป๐ฎ๐น ๐ฑ๐ฎ๐๐ฎ, strict governance, and zero tolerance for pipeline failures are the daily reality.
My specialty is building systems that are ๐ฎ๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐ฒ๐ฑ ๐ฝ๐ฟ๐ผ๐ฝ๐ฒ๐ฟ๐น๐ ๐ณ๐ฟ๐ผ๐บ ๐๐ต๐ฒ ๐๐๐ฎ๐ฟ๐ metadata-driven, layered, monitored, and built to scale.
๐ช๐๐๐ง ๐ ๐๐จ๐๐๐
โฆ ๐ ๐ฒ๐๐ฎ๐ฑ๐ฎ๐๐ฎ-๐๐ฟ๐ถ๐๐ฒ๐ป ๐๐ง๐/๐๐๐ง ๐ฃ๐ถ๐ฝ๐ฒ๐น๐ถ๐ป๐ฒ๐
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 ๐ฏ๐ด% on a production enterprise warehouse by eliminating redundant mapping layers.
โฆ ๐๐ป๐๐ฒ๐ฟ๐ฝ๐ฟ๐ถ๐๐ฒ ๐๐ฎ๐๐ฎ ๐ช๐ฎ๐ฟ๐ฒ๐ต๐ผ๐๐๐ฒ ๐๐ฒ๐๐ถ๐ด๐ป
End-to-end warehouse design across ๐ฆ๐๐ฎ๐ด๐ถ๐ป๐ด โ ๐๐ผ๐ฟ๐ฒ โ ๐๐ผ๐น๐ฑ (Medallion Architecture), with star/snowflake schema modeling, incremental loading, duplicate handling, and structured audit logging baked in.
โฆ ๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ผ๐ณ๐ ๐๐ฎ๐ฏ๐ฟ๐ถ๐ฐ ๐ฆ๐ผ๐น๐๐๐ถ๐ผ๐ป๐
Lakehouse and Warehouse design on OneLake, Fabric Data Factory pipelines, semantic models with ๐ฅ๐ผ๐-๐๐ฒ๐๐ฒ๐น ๐ฆ๐ฒ๐ฐ๐๐ฟ๐ถ๐๐ (๐ฅ๐๐ฆ), and report publishing as Fabric Apps for internal teams and external stakeholders.
โฆ ๐๐๐๐ฟ๐ฒ & ๐๐ฎ๐๐ฎ๐ฏ๐ฟ๐ถ๐ฐ๐ธ๐ ๐ฃ๐ถ๐ฝ๐ฒ๐น๐ถ๐ป๐ฒ๐
ADF orchestrated cloud pipelines and PySpark based distributed data processing on Databricks for large-scale, partitioned datasets.
โฆ ๐ฃ๐ผ๐๐ฒ๐ฟ ๐๐ & ๐ฆ๐ฆ๐ฅ๐ฆ ๐ฅ๐ฒ๐ฝ๐ผ๐ฟ๐๐ถ๐ป๐ด
Semantic model design, DAX measures, drill-through dashboards, RLS enforcement, SSRS and Report Builder reports, and Fabric App deployment for enterprise stakeholders.
โฆ ๐๐ฒ๐ด๐ฎ๐ฐ๐ ๐ ๐๐ฆ ๐ ๐ถ๐ด๐ฟ๐ฎ๐๐ถ๐ผ๐ป
Migrated 20+ reports from legacy systems into a centralized, modern BI architecture without disrupting ongoing operations.
๐ฅ๐๐๐๐ก๐ง ๐ฅ๐๐ฆ๐จ๐๐ง๐ฆ
โข Reduced ETL runtime by ๐ฏ๐ด% (4 hrs โ 2.5 hrs) by optimizing metadata-driven SSIS pipelines
โข Built automated SFTP ingestion pipelines with archive logic to ensure ๐ถ๐ป๐ฐ๐ฟ๐ฒ๐บ๐ฒ๐ป๐๐ฎ๐น, ๐ฑ๐๐ฝ๐น๐ถ๐ฐ๐ฎ๐๐ฒ-๐ณ๐ฟ๐ฒ๐ฒ data loading
โข Delivered ๐บ๐๐น๐๐ถ๐ฝ๐น๐ฒ ๐๐ป๐๐ฒ๐ฟ๐ฝ๐ฟ๐ถ๐๐ฒ ๐๐ฎ๐๐ฎ ๐ช๐ฎ๐ฟ๐ฒ๐ต๐ผ๐๐๐ฒ๐ supporting different business products across fintech, billing, and payments
โข Published ๐ญ๐ฑ+ ๐ฃ๐ผ๐๐ฒ๐ฟ ๐๐ ๐ฟ๐ฒ๐ฝ๐ผ๐ฟ๐๐ as Fabric Apps with Row Level Security for external stakeholders
โข Onboarded 10+ new source tables into a redesigned data warehouse while improving ETL performance and storage efficiency
โข Worked extensively with ๐ง๐-๐๐ฐ๐ฎ๐น๐ฒ ๐๐ฟ๐ฎ๐ป๐๐ฎ๐ฐ๐๐ถ๐ผ๐ป๐ฎ๐น ๐ฑ๐ฎ๐๐ฎ in a high-volume payment processing environment.
๐๐ข๐ฅ๐ ๐ฆ๐ง๐๐๐
๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ผ๐ณ๐ ๐๐ฎ๐ฏ๐ฟ๐ถ๐ฐ | ๐๐๐๐ฟ๐ฒ ๐๐ฎ๐๐ฎ ๐๐ฎ๐ฐ๐๐ผ๐ฟ๐ | ๐๐๐๐ฟ๐ฒ ๐๐ฎ๐๐ฎ๐ฏ๐ฟ๐ถ๐ฐ๐ธ๐ | ๐ฃ๐๐ฆ๐ฝ๐ฎ๐ฟ๐ธ | ๐๐ฝ๐ฎ๐ฐ๐ต๐ฒ ๐ฆ๐ฝ๐ฎ๐ฟ๐ธ | ๐ฆ๐ฆ๐๐ฆ | ๐ฆ๐ค๐ ๐ฆ๐ฒ๐ฟ๐๐ฒ๐ฟ | ๐ข๐ฟ๐ฎ๐ฐ๐น๐ฒ | ๐ฃ๐ผ๐๐๐ด๐ฟ๐ฒ๐ฆ๐ค๐ | ๐ฃ๐ผ๐๐ฒ๐ฟ ๐๐ | ๐ฆ๐ฆ๐ฅ๐ฆ | ๐ง-๐ฆ๐ค๐ | ๐ฃ๐/๐ฆ๐ค๐ | ๐๐ฎ๐๐ฎ ๐ช๐ฎ๐ฟ๐ฒ๐ต๐ผ๐๐๐ถ๐ป๐ด | ๐ ๐ฒ๐ฑ๐ฎ๐น๐น๐ถ๐ผ๐ป ๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ | ๐ฆ๐๐ฎ๐ฟ ๐ฆ๐ฐ๐ต๐ฒ๐บ๐ฎ | ๐ฆ๐ป๐ผ๐๐ณ๐น๐ฎ๐ธ๐ฒ ๐ฆ๐ฐ๐ต๐ฒ๐บ๐ฎ | ๐๐ง๐/๐๐๐ง | ๐๐ฎ๐ธ๐ฒ๐ต๐ผ๐๐๐ฒ
๐๐๐ฆ๐ง-๐๐๐ง ๐ฃ๐ฅ๐ข๐๐๐๐ง๐ฆ
โข Data warehouse or lakehouse design from scratch
โข ETL/ELT pipeline build, optimization, or troubleshooting
โข Microsoft Fabric or Azure migration from legacy on-prem systems
โข Power BI, SSRS, or Fabric App reporting solutions
โข SQL performance tuning, stored procedures, and indexing
โข Production pipeline monitoring, job scheduling, and failure resolution
๐๐ข๐ช ๐ ๐ช๐ข๐ฅ๐
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 ๐น๐ผ๐ด๐ด๐ถ๐ป๐ด, ๐ฒ๐ฟ๐ฟ๐ผ๐ฟ ๐ต๐ฎ๐ป๐ฑ๐น๐ถ๐ป๐ด, and ๐ท๐ผ๐ฏ ๐๐ฐ๐ต๐ฒ๐ฑ๐๐น๐ถ๐ป๐ด built in from day one, not added as an afterthought.
๐ฉ ๐ฆ๐ฒ๐ป๐ฑ ๐บ๐ฒ ๐ฎ ๐บ๐ฒ๐๐๐ฎ๐ด๐ฒ ๐๐ถ๐๐ต ๐๐ผ๐๐ฟ ๐ฝ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐ ๐ฑ๐ฒ๐๐ฎ๐ถ๐น๐. ๐ ๐ฟ๐ฒ๐๐ฝ๐ผ๐ป๐ฑ ๐พ๐๐ถ๐ฐ๐ธ๐น๐ ๐ฎ๐ป๐ฑ ๐๐ถ๐น๐น ๐ผ๐๐๐น๐ถ๐ป๐ฒ ๐ฎ ๐ฐ๐น๐ฒ๐ฎ๐ฟ ๐ฎ๐ฝ๐ฝ๐ฟ๐ผ๐ฎ๐ฐ๐ต ๐ณ๐ผ๐ฟ ๐๐ผ๐๐ฟ ๐ฝ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐.
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
Arpit K.
Chennai, India
$11/hr
5.0
2 jobs
๐ GCP Certified Data Engineer | Google Cloud Platform | Python | SQL | Airflow | GCP workflows | Bigquery | DataForm | Power BI
With a solid foundation in GCP (Google Cloud Platform) and a certification in Data Engineering, I bring a wealth of expertise to the table. As a Senior Data Engineer with ~5 years of industry experience, including working in both product-based and service-based companies, I excel in leveraging cutting-edge technology to deliver innovative solutions.
๐น Skills Highlights:
GCP Expertise: Proficient in leveraging the power of Google Cloud Platform for data engineering tasks, ensuring efficient and scalable solutions.
Python & PySpark: Adept at harnessing the capabilities of Python and PySpark to manipulate and analyze large datasets, driving actionable insights.
SQL Mastery: Experienced in crafting complex SQL queries and optimizing database performance for streamlined data operations.
Airflow expertise: Experienced with Apache Airflow, building ETL pipelines, managing task dependencies, and deploying and monitoring workflows.
Power BI & Alteryx: Skilled in creating visually compelling dashboards and automating workflows using Power BI and Alteryx, empowering stakeholders with actionable insights.
Problem-Solving: Known for my analytical mindset and ability to tackle complex challenges head-on, I thrive in dynamic environments where innovative solutions are required
BigQuery
SQL
Python
Data Engineering
Google Cloud Platform
ETL Pipeline
Data Warehousing
Apache Spark
Apache Airflow
Databricks Platform
PySpark
Computer Vision
Parikshit M.
Patiala, India
$10/hr
5.0
3 jobs
As a Machine Learning Engineer & Data Analyst with 5+ years of industry experience, I specialize in building end-to-end ML pipelines, transforming complex datasets into actionable insights, and deploying scalable data solutions across cloud platforms. I've worked across the full ML lifecycle from raw data ingestion to model deployment helping businesses make smarter, faster decisions.
โ Data Analysis & Dashboard Storytelling I don't just build dashboards I turn raw, messy data into compelling visual stories that drive decisions using Power BI, Apache Superset, and Excel. I design interactive dashboards that go beyond charts clearly showing what the numbers mean, what's trending, and what actions to take next.
โ Machine Learning & Predictive Modeling Developed ML models for use cases including ethnicity prediction using US Census data, product likelihood scoring, and balance sheet forecasting with Time Series models. Applied classification, regression, clustering, and NLP algorithms using Python, PySpark, and XGBoost. Leveraged AutoML and Hyperopt for model selection and hyperparameter tuning, optimizing for F1 scores. Managed experiment tracking and model registration using MLflow.
โ MLOps & Pipeline Orchestration Designed and deployed scalable ML pipelines using Azure Data Factory (ADF) and Databricks, with seamless integration with ServiceNow and email alerts. Built Feature Pipelines creating Silver and Gold layer tables. Applied OOP principles and PySpark pipeline wrappers for production-grade inference. Experienced with Docker, Evidently, and MLflow for end-to-end MLOps.
โ Cloud Platforms Hands-on experience across Azure (DevOps, Data Factory, Databricks), GCP (Cloud Run, Cloud Build, BigQuery, Artifact Registry), AWS (Databricks, S3), and Snowflake for scalable data and ML workloads.
โ NLP & Text Analysis Applied NLP techniques including sentiment detection, keyword extraction, and text classification using Python. Experienced in building models for text categorization.
โ Web App Development & Deployment Built and deployed a Market Mix Modelling web application on GCP Cloud Run using Flask and Node.js, enabling marketing budget allocation across social media platforms with full cloud infrastructure support.
Tech Stack at a Glance: Power BI ยท Apache Superset ยท Python ยท PySpark ยท SQL ยท MLflow ยท XGBoost ยท Scikit-learn ยท FastAPI ยท Flask ยท Azure ADF ยท Databricks ยท GCP ยท Snowflake ยท Docker ยท Hyperopt ยท AutoML
Let's connect and build intelligent, data-driven solutions for your business!
Python
Data Analytics
SQL
Machine Learning
Data Analysis
Microsoft Power BI
MySQL
Game Testing
PySpark
Apache Superset
MLflow
XGBoost
Python Scikit-Learn
FastAPI
Flask
Microsoft Azure
Databricks Platform
Snowflake
Docker
Google AutoML
Mochammad Arie N.
Jakarta, Indonesia
$15/hr
5.0
7 jobs
Most data pipelines donโt fail because of code. They fail because they weren't built for scale.
With 5+ years of experience engineering data systems at companies like Danone and Zurich, I help businesses transform fragile prototypes into resilient, production-grade infrastructure.
I donโt just move data; I build the "Source of Truth" that leadership and AI systems actually trust.
โ Productionizing AI Pipelines: Hardening Python prototypes into scalable RAG and LLM infrastructures (Azure).
โ Infrastructure-as-Code: Building automated, modular ETL/ELT pipelines that don't require daily manual fixes.
โ The "One-Source" Dashboard: Integrating messy data from APIs, SaaS (Shopify, HubSpot), and databases into clean Snowflake/BigQuery layers.
โ Performance Recovery: Optimizing slow SQL queries and high-cost cloud warehouses to save you thousands in monthly spend.
โ Technical Writing for Data & AI Teams: Creating product documentation, implementation guides, architecture documentation, data dictionaries, knowledge bases, and thought leadership content that makes complex systems easier to understand and adopt.
๐ Tech Stack
Languages: Python (FastAPI, Pandas, PySpark), SQL
Data Engineering: ETL/ELT Pipelines, Data Warehousing, Data Modeling, Data Quality, Data Governance
Cloud & Warehousing: Snowflake, BigQuery, Databricks, Azure Data Factory, Azure Data Lake, AWS (S3, Athena, Glue)
Orchestration & Transformation: Apache Airflow, dbt
Analytics & BI: Tableau, Power BI
Development & Collaboration: Git, GitHub, VS Code
Data Ops: API Integrations, Data Validation, Workflow Automation
Technical Writing: Product Documentation, API Documentation, User Guides, Knowledge Bases, Data Dictionaries, Technical Blog Content
โ Why Me?
5+ Years Experience: I've seen what breaks at the enterprise level and how to prevent it in your startup.
Hands-On Builder & Technical Writer: I can both build the system and explain it clearly to engineers, stakeholders, and customers.
Speed over Perfection: I focus on shipping high-impact systems that drive revenue, not just technical documentation.
Transparent Communication: You get regular updates and a partner who challenges requirements to find better solutions.
Ready to clean up your data debt?
Data Engineering
Python
SQL
ETL Pipeline
Databricks Platform
Snowflake
dbt
Apache Airflow
BigQuery
Data Migration
LLM Prompt
AI Content Writing
Microsoft Power BI
Machine Learning
Microsoft Azure
Data Warehousing & ETL Software
Technical Writing
Microsoft Power Automate
Data Warehousing
Azure Service Fabric
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