Azure Data Engineer – Azure ADF, PySpark, Databricks (Ongoing Work

looking for an experienced Azure Data Engineer to support and enhance our existing data platform on an ongoing basis.

You should be strong in:

Azure Data Factory (ADF) for building and maintaining ETL/ELT pipelines

Azure Databricks and PySpark for large‑scale data processing

Python for data engineering utilities, automation, and integration

Delta Lakes/Lakehouse concepts, performance optimization, and troubleshooting

Working with SQL‑based data sources, data warehousing, and BI integrations

Responsibilities

Design, build, and optimize data pipelines in Azure ADF and Databricks

Develop and maintain PySpark and Python jobs for batch and near real‑time workloads

Implement best practices for data quality, observability, and monitoring

Collaborate with our internal team, follow existing standards, and document your work

Support and improve existing pipelines, diagnose issues, and propose scalable solutions

Nice to have

Experience with Azure Synapse or similar MPP data warehouses

CI/CD for data pipelines (Git, Azure DevOps, etc.)

Basic understanding of data modeling and BI/reporting needs

Engagement details

Remote, long‑term engagement

20–30 hrs/week

Working hours with some overlap with 6 PM – 2 AM PKT preferred

Budget: 2–8 USD/hour, depending on experience and fit

When you apply, please answer briefly:

Relevant Azure ADF / Databricks projects you’ve done (1–2 examples).

Your hourly rate within 2–8 USD/hour.

Your typical availability per week and time‑zone.

A short note on how you approach debugging and optimizing slow pipelines.