Databricks Engineer

Job Summary

Job Title: Databricks Engineer

Experience Level: 5 - 10 years

Location: Hyderabad / Pune

Qualification: BTech/MTech/MCA

Mode of Work: Hybrid

We are seeking a skilled and motivated Databricks Engineer to design, develop, and optimize scalable data solutions on the Databricks platform. The ideal candidate will have strong expertise in Apache Spark, Databricks architecture, ETL development, and modern data lakehouse concepts. This role will be responsible for building robust data pipelines, implementing best practices in data engineering, and supporting analytics and machine learning workloads.

Key Responsibilities

• Design, develop, and maintain scalable data engineering solutions using Databricks and Apache Spark.
• Create and deploy custom ETL/ELT pipelines to ingest, transform, and process large volumes of structured and unstructured data.
• Configure, manage, and optimize Databricks clusters for performance, scalability, and cost efficiency.
• Implement and manage Lakehouse architectures using Databricks best practices.
• Develop and maintain data workflows utilizing Delta Lake and Delta Live Tables (DLT).
• Design and implement Medallion Architecture (Bronze, Silver, Gold layers) for reliable and scalable data processing.
• Configure and govern data assets using Unity Catalog, ensuring data security, access control, and compliance.
• Collaborate with data architects, analysts, and business stakeholders to translate business requirements into technical solutions.
• Monitor data pipelines and troubleshoot performance or data quality issues.
• Optimize Spark jobs and workflows to improve processing efficiency and reduce execution time.
• Follow DevOps and CI/CD best practices for deployment and release management.

Requirements

• 5-10 years of experience in Data Engineering or Big Data technologies.
• Strong understanding of Databricks architecture and core platform capabilities.
• Hands-on experience in setting up and managing Databricks clusters.
• Strong expertise in Apache Spark (PySpark/Scala Spark).
• Experience developing and deploying custom ETL pipelines in Databricks.
• Experience implementing Medallion Architecture within Databricks.
• Hands-on experience with Delta Live Tables (DLT).
• Strong understanding and implementation experience with Unity Catalog.
• Experience working with Delta Lake and Lakehouse architecture principles.
• Knowledge of data modeling, data quality, and performance tuning techniques.
• Familiarity with version control tools such as Git.

Qualifications

Job Type

Full time

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