Design and maintain data pipelines for enterprise analytics and reporting, using SQL Server and Azure technologies. Collaborate with stakeholders to ensure data quality and performance optimization.
Responsibilities
Design, build, and maintain data pipelines and infrastructure supporting enterprise analytics and reporting
Develop and maintain incremental data pipelines using SSIS, PySpark notebooks, and Python
Implement and optimize ETL/ELT processes for Azure SQL databases and data lake environments
Build meta-driven, scalable data ingestion frameworks supporting SCD Type 2 methodology
Write and optimize T-SQL stored procedures, views, and dynamic SQL for data transformations
Develop Python-based automation including Azure Functions, blob triggers, and API integrations
Maintain data quality, perform root cause analysis, and resolve data pipeline issues
Support CI/CD processes including code reviews, Git version control, and Azure DevOps workflows
Monitor pipeline performance and implement optimization strategies
Assist with data modeling, indexing strategies, and schema evolution
Collaborate with business stakeholders and Analytics team to meet reporting requirements
Participate in data platform modernization and improvement initiatives
Requirements
Proficiency with SQL Server, T-SQL, and database concepts (indexing, query optimization)
Experience with ETL/ELT tools and concepts (SSIS or similar preferred)
Understanding of data warehousing, dimensional modeling, and SCD methodologies
Familiarity with Azure cloud services (especially Azure SQL Database)
Ability to troubleshoot data issues and perform data analysis
Strong problem-solving skills and attention to detail
Experience with version control (Git) and collaborative development
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