We're hiring 3 Data Engineers to build and scale an enterprise Cloud Data Lakehouse on Azure Databricks + ADLS Gen2. You'll own pipelines end-to-end — from raw ingestion through Bronze/Silver/Gold — and work directly with data scientists, analytics engineers, and business stakeholders. This is a hands-on engineering role, not a notebook-only role. If you write modular, tested, version-controlled Python and care about what a job costs to run, you'll fit. What you'll do

Build scalable batch and streaming pipelines with PySpark, Spark SQL, and Databricks

Orchestrate workflows via Azure Data Factory, Databricks Workflows, and Delta Live Tables

Implement Medallion Architecture on Delta Lake — partitioning, schema enforcement, data quality expectations

Tune clusters, jobs, and queries to kill bottlenecks and cut cloud spend

Enforce row/column-level access and lineage through Unity Catalog

Ship via Azure DevOps or GitHub Actions with real CI/CD and test coverage





Deliver clean Gold-layer datasets for ML models and Power BI

What we're looking for (3–5 years)

Hands-on Azure Databricks, Apache Spark (PySpark/Spark SQL), Delta Lake

Azure core: ADLS Gen2, ADF, Key Vault

Strong Python + advanced SQL (window functions, complex joins, query tuning)

Dimensional modelling (Star/Snowflake) and Medallion Lakehouse patterns

Git, code reviews, modular Python outside notebooks, basic CI/CD

Bachelor's in CS/IT or equivalent practical experience

Transparent communication with non-technical stakeholders Nice to have

Unity Catalog · Kafka or Azure Event Hubs · Terraform/Bicep · Databricks Certified Data Engineer Associate Details

Remote (India) · Full-time · 3 positions - Immediate joiner only To apply: [Apply here or [email protected] ] — subject line "Azure DE — [Your Name]"

📌 Azure Data Engineer (Databricks) — Remote, India
🏢 Zoft AI
📍 India