Databricks SQL Engineer

Job Description

- Years of Experience : 5+ years ( PHARMA MANDATORY )

- Role Type : Fixed Term Contract (6 Months)

- Payroll Organization : Talpro

- Shift Timing : Day shift IST, from 12pm

- Notice Period : Immediate Joiners Only

- Work Location : Mumbai / Pune / Bangalore / Chennai / Ahmedabad / Noida (Chennai Most Preferred)

- Work Mode : Hybrid (3 Days from Office Weekly)

Mandatory Skills :

- Databricks

- SQL

- PySpark

- Pharma or Life Sciences domain experience

Good to Have Skills :

- Delta Lake

- Data Lakehouse Architecture

- Unity Catalog or similar data governance tools

- SQL development & performance tuning with large datasets

- Git for version control

- CI/CD for data pipelines (Databricks Repos, Terraform, dbx)

- Azure Databricks or Databricks on AWS

- Python for data manipulation

- Structured streaming in Spark

- Azure Purview or equivalent governance tools

- Automation experience with Terraform/dbx

- Databricks Notebooks

- Data documentation and dictionary practices

Role Overview / Job Summary :

We are looking for an experienced Databricks SQL Engineer with a Pharma or Life Sciences background to join our offshore Data Engineering team.

This role focuses on building efficient, scalable SQL-based data models and pipelines using Databricks SQL, Spark SQL, and Delta Lake.

The ideal candidate will play a key role in transforming raw data into valuable analytical insights, enabling critical decision-making across pharma-related business functions.

Key Responsibilities / Job Responsibilities :

- Design and optimize SQL queries and data models in Databricks for large-scale datasets

- Develop and maintain robust ETL/ELT pipelines using Databricks workflows

- Implement Delta Lake and Unity Catalog for secure and governed data assets

- Ensure data quality via validation, testing, and monitoring mechanisms

- Optimize performance and cost for the data lakehouse environment

- Collaborate with stakeholders to support analytics and business needs

- Deploy notebooks and SQL workflows using CI/CD best practices

- Document pipelines, queries, and data models to foster self-service