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-Solid 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.
Solid understanding of Medallion Architecture and Delta Lake.
Advanced SQL and experience working with large-scale datasets.

Positive 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,

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