Senior Data Engineer (AWS, Databricks, India)

This is a remote position.

We are looking for 2 Senior Data Engineers to design, build, and maintain scalable data pipelines that power analytics, reporting, and machine learning use cases.

You will work with Python, Databricks, AWS, Spark/PySpark, SQL, Docker, Git, and CI/CD tools to move data from different source systems into a data lake and data warehouse. This role is a good fit for someone who enjoys both engineering quality and business impact: clean data models, reliable pipelines, strong documentation, and data that other teams can actually use.

You will collaborate closely with Product Analysts, Data Scientists, and ML Engineers to make data accessible, trusted, and understandable across the organization.

What you will work on

You will:

• Design, build, and maintain ETL/ELT pipelines using Python and Databricks

• Extract, transform, and load data from multiple source systems into the data lake and data warehouse

• Create data transformation rules and data models for analytics and reporting

• Implement data quality checks, logging, monitoring, and orchestration practices

• Maintain data catalogues and support clear data lineage

• Work with Product Analysts, Data Scientists, and ML Engineers to improve data availability and usability

• Use test-driven development practices where relevant

• Work with Git-based version control, branching strategies, Docker, and CI/CD tools

• Prepare and maintain clear technical and SDLC documentation

Requirements

• 7+ years of relevant data engineering experience

• Strong hands-on experience with Python

• Practical ETL/ELT experience on Databricks

• Strong knowledge of AWS cloud services

• Solid database experience and strong SQL skills

• 2–3 years of Spark/PySpark experience

• Experience with Git, Docker, and CI/CD tools

• Good understanding of SDLC documentation

• Ability to communicate clearly with engineering, analytics, and data science teams

• Experience in healthcare, pharma or similar.