Senior Data Engineer

Senior Data Engineer - Databricks | PySpark | dbt | Lakehouse Engineering

⚠️ This is NOT a typical Data Engineering position.

We are looking for a hands-on Senior Data Engineer with strong, production-grade Databricks experience - someone who has actually built and optimized Lakehouse/Medallion architectures, PySpark & dbt pipelines, PostgreSQL data layers, and CI/CD workflows, rather than someone with only surface-level exposure to these technologies.

⚠️ If Databricks is not a core part of your recent hands-on experience, this role may not be the right fit.

Job Title: Senior Data Engineer

Specialization: Data Engineering | Databricks | Lakehouse | Data Platforms | AI-Ready Data

Experience: 5+ Years

Location: BNG | HYD | PUN | MUM | GGN

Work Model: Hybrid

What We're Looking For

Mandatory-Strong hands-on experience required:

• Databricks – with practical experience building production data platforms and Lakehouse architectures.

• PySpark – strong production experience working with non-trivial data volumes.

• Python – advanced programming and data engineering experience.

• dbt – hands-on experience with staging, transformations, incremental models, testing, and documentation.

• CI/CD – Azure DevOps – experience deploying and managing data assets through CI/CD pipelines.

• PostgreSQL – database design, schema management, query optimization, and performance tuning.

• Strong understanding of Medallion Architecture and Delta Lake.

• Advanced SQL and experience working with large-scale datasets.

Good to Have

• MLflow and experience supporting ML/data science workflows.

• LangChain or similar AI/Agent frameworks.

• Exposure to AI Agents / AI-ready data platforms.

• Experience with SQL Server.

• Experience with DuckDB.

• Terraform / Infrastructure-as-Code exposure.

• Docker and containerized data workloads.

• Experience with APIs and structured/semi-structured formats such as JSON, CSV, Parquet, and Apache Arrow.

• Exposure to marketing analytics, marketing measurement, or enterprise consulting environments.

Why This Role Is Different

This isn't simply a role where you'll “build pipelines and move data.”

You'll be responsible for building the data foundation behind modeling, optimization, analytics, customer-facing applications, and AI Agents - with an emphasis on architecture, performance, data quality, governance, reproducibility, and production reliability.

Primary Skills (Mandatory):

Databricks | PySpark | Python | dbt | Azure DevOps / CI-CD | PostgreSQL | Advanced SQL | Delta Lake | Medallion Architecture

Good to Have:

MLflow | LangChain | AI Agents | SQL Server | DuckDB | Terraform | Docker