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Job description
Design and implement end-to-end data architecture using Databricks Lakehouse platform
Define data engineering best practices and build scalable ETL/ELT pipelines
Architect solutions leveraging Apache Spark (PySpark/Scala) and Databricks workflows
Implement Delta Lake for data reliability, performance, and governance
Collaborate with stakeholders to understand business requirements and translate them into technical solutions
Optimize performance, cost, and scalability of data pipelines
Provide technical leadership , mentoring data engineers and developers
Ensure data security, governance, and compliance standards are met
Integrate Databricks with cloud services (Azure, AWS, or GCP) and other enterprise systems
Support real-time and batch data processing use cases
Required Skills & Qualifications
Technical Skills
Strong hands-on experience with Databricks Platform
Expertise in Apache Spark (PySpark / Scala / SQL)
Experience with Delta Lake, Unity Catalog, and Lakehouse architecture
Proficiency in data pipelines, ETL/ELT frameworks
Strong experience in SQL and data modeling
Hands-on experience with cloud platforms: Azure (ADF, ADLS, Synapse) OR
AWS (S3, Glue, EMR) OR
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Who can apply
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