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About the Role:

As part of our Innovation Team , we are seeking a C ertified Senior Databricks Engineer / Tech Lead with 7\u20138 years of hands-on experience in building scalable data platforms. This role will focus on designing, building, and operationalizing data solutions on the Databricks platform to accelerate advanced analytics and AI use cases.

Key Responsibilities:

Architect, develop, productionize and maintain end to end solutions in Databricks

Implement and optimize ETL/ELT processes for structured and semi-structured data

Leverage Delta Lake for ACID transactions, data versioning, and time-travel features

Drive adoption of the Lakehouse architecture to unify data warehousing and AI/ML workloads

Implement CI/CD pipelines using Databricks Repos , Asset Bundles , and integration with DevOps tools

Configure and enforce Unity Catalog for secure, governed access to data assets

Design and implement data quality and validation frameworks to ensure trusted data

Lead performance tuning and optimization efforts for Spark jobs and queries

Integrate with external systems such as Kafka , Event Hub , and REST APIs for real-time and batch processing

Collaborate with data scientists and business stakeholders to build feature-rich datasets and reusable assets

Troubleshoot and debug complex data workflows in development and production environments

Guide junior engineers and contribute to best practices in data engineering and platform usage

Ensure platform security, access controls , and compliance with enterprise data governance standards.

Required Skills:

Expertise in Apache Spark and Databricks platform

Experience with Databricks Lakehouse architecture

Delta Lake concepts

Proficient in PySpark, SQL, and Delta Lake

Strong knowledge of Data Engineering concepts

Experience with data ingestion, ETL/ELT pipelines

Familiarity with Unity Catalog and data governance

Hands-on with Databricks Notebooks and Jobs

CI/CD automation with Databricks Repos and DevOps, Asset Bundles

Databricks Asset Bundle implementation knowledge

Strong understanding of performance tuning in Spark

Data quality and validation framework implementation

Experience in handling structured, semi-structured data

Proficient in debugging and troubleshooting

Collaboration with data scientists and analysts

Good understanding of security and access control

Experience with Mosaic AI or Databricks ML capabilities

Exposure to streaming pipelines using Structured Streaming

Familiarity with data observability and lineage tools.

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Senior Databricks Engineer / Tech Lead