Senior Data Engineer - Databricks | Py Spark | 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, Py Spark & dbt pipelines, Postgre SQL 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. Py Spark – 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 Dev Ops – experience deploying and managing data assets through CI/CD pipelines. Postgre SQL – 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. Good to Have
MLflow and experience supporting ML/data science workflows. Lang Chain or similar AI/Agent frameworks. Exposure to AI Agents / AI-ready data platforms. Experience with SQL Server. Experience with Duck DB. 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 environment

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