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.