This role focuses on designing, developing, and optimizing data solutions within the Azure ecosystem. You will be instrumental in building robust data integration processes and scalable data lake architectures.

The position involves working with enterprise data platforms and ensuring the quality, availability, and reliability of data across analytics environments. Adherence to best practices in data warehousing, ETL optimization, and performance tuning is key.

Key responsibilities include developing and optimizing solutions using Azure Synapse Analytics, and building data integration pipelines with Azure Data Factory.

You will design and implement scalable Data Lake architectures (ADLS Gen2) and create high-performance ETL/ELT frameworks. Monitoring and troubleshooting large-scale data workloads are also crucial.

This role requires identifying performance bottlenecks and implementing optimization strategies for data movement and transformation. Ensuring data quality and reliability across analytics ecosystems is a primary focus, aligning with established data warehousing and Synapse performance tuning practices.

Advanced SQL query analysis and optimization are essential. You will analyze and tune execution plans for complex analytical workloads and configure Synapse Dedicated SQL Pools.

Designing and implementing efficient partitioning strategies for large datasets is expected. This includes optimizing indexing, statistics, and workload distribution to enhance performance.