Architect, design, and implement scalable data platforms and pipelines on Azure and Databricks.
• Build and optimize data ingestion, transformation, and processing workflows across batch and real-time data streams.
• Work extensively with ADLS, Delta Lake, and Spark (Python) for large-scale data engineering.
• Lead the development of complex ETL/ELT pipelines, ensuring high quality, reliability, and performance.
• Design and implement data models, including conceptual, logical, and physical models for analytics and operational workloads.
• Work with relational and lakehouse systems including PostgreSQL and Delta Lake.
• Define and enforce best practices in data governance, data quality, security, and architecture.
• Collaborate with architects, data scientists, analysts, and business teams to translate requirements into technical solutions.
• Troubleshoot production issues, optimize performance, and support continuous improvement of the data platform.
• Mentor junior engineers and contribute to building engineering standards and reusable components.
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