Roles and Responsibilities

• Design scalable data lake/lakehouse architectures using Databricks and cloud-native services
• Build and optimize ETL/ELT pipelines and metadata-driven ingestion frameworks
• Define and enforce data governance, quality, and integrity standards
• Architect AI-enabled data solutions, including RAG workflows
• Lead cloud migrations from legacy systems to modern data platforms
• Optimize data performance, cost, and reliability
• Provide architectural guidance, reusable patterns, and documentation

Required Skills & Experience

• Strong experience with Azure or AWS and Databricks
• Proficiency in Python and SQL
• Expertise in ETL/ELT pipelines, ADF workflows, and data lake architectures
• Experience with CI/CD, DevOps, and Git-based development
• Ability to translate business requirements into technical solutions

Technical Stack

• Programming: Python, SQL, R
• Big Data: Spark, Hadoop, Kafka, Hive
• Cloud: Azure (ADF, Databricks, Azure OpenAI), AWS
• Data Warehousing: Redshift, SQL Server
• ETL Tools: SSIS

Education & Experience

• Bachelor’s degree in a related field
• 6+ years of experience in data engineering or .NET development.

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