Databricks engineer

Job Description – Databricks Engineer

Location:

Andheri, Mumbai

Employment Type:

Full-Time | Work from Office

Experience:

5–7 Years
Function:  IT
Industry:  Pharmaceutical
About the Role
We are looking for an experienced  Databricks Engineer  to join our Data Engineering team and play a key role in designing, developing, and optimizing scalable data solutions.
The ideal candidate will have strong hands-on experience with  Databricks, Python, PySpark, SQL, Apache Spark, and Azure cloud data platforms , along with a solid understanding of modern data architecture, governance, and data engineering best practices.
Experience in the  pharmaceutical industry or pharma business processes  will be an added advantage.

Key Responsibilities
Design, develop, and maintain scalable and reliable data engineering solutions using  Databricks, Python, PySpark, SQL, and Apache Spark .
Build and optimize  Databricks notebooks, clusters, Jobs, Workflows, and SQL Warehouses .
Develop efficient data pipelines and transformation frameworks for large-scale data processing.
Work with  Delta Lake, Lakehouse architecture, Medallion architecture (Bronze, Silver, Gold) , and modern data-modeling practices.
Optimize Spark jobs, queries, clusters, and data pipelines for  performance, scalability, and cost efficiency .
Develop and maintain data pipelines using  Azure Data Factory, Airflow, and dbt .
Work with Azure storage, identity, networking, and security services to build secure and scalable data solutions.
Implement and manage  Git-based version control and CI/CD pipelines  for data engineering workflows.
Work with  Unity Catalog  for data governance, access management, lineage, and discoverability.
Ensure data quality, reliability, security, and compliance across data pipelines and platforms.
Collaborate with business, analytics, technology, and cross-functional teams to understand requirements and deliver effective data solutions.
Troubleshoot data pipeline issues and proactively identify opportunities for process and performance improvements.
Contribute to data engineering standards, best practices, documentation, and continuous improvement initiatives.
Required Skills & Expertise
Strong hands-on experience with  Databricks  and Apache Spark.
Advanced proficiency in  Python, PySpark, and SQL .
Strong understanding of  Delta Lake, Lakehouse architecture, Medallion architecture, and data modelling .
Experience working with Databricks  Notebooks, Clusters, Jobs, Workflows, and SQL Warehouses .
Good understanding of  Azure cloud data services , including storage, identity, networking, and security.

Experience with  Azure Data Factory, Airflow, dbt, Git, and CI/CD .
Knowledge of  Unity Catalog, data governance, lineage, data quality, and performance tuning .
Strong analytical and problem-solving skills.
Good communication and stakeholder-management skills.
Ability to work effectively in a  full-time work-from-office environment .
Experience & Qualification
Years of

Experience:

5–7 Years
Relevant

Experience:

Minimum 3–5 years of hands-on data engineering experience, including Databricks implementation and delivery.
Educational

Qualification:

BE /

B. Tech. / MCA in Computer Science, Information Technology, Engineering, or a related discipline.
Additional

Qualification:

Databricks certification  is preferred.
Experience or knowledge of  pharmaceutical processes and business functions  will be an added advantage.

What We Offer
️  Free Gym Facility  – Supporting employee health and wellness.
Subsidized Food  – Convenient and affordable meals at the workplace.
Opportunity to Work on Meaningful Data Initiatives  – Exposure to enterprise-scale data engineering, analytics, and digital transformation projects.
Collaborative Work Environment  – Work alongside experienced technology and business teams on impactful projects.