Description

• Design, build, and maintain data pipelines using Azure Data Factory (ADF)
• Develop and implement incremental data processing patterns, including UPSERT/MERGE logic
• Ingest and transform data from Oracle EBS into Azure SQL and Snowflake
• Integrate REST API-based data sources into enterprise data pipelines
• Design and maintain data warehouse and data mart structures (star/snowflake schemas)
• Transform and normalize semi-structured data (JSON) into relational models
• Optimize performance for large-scale datasets (indexing, partitioning, query tuning)
• Establish standards for data modeling, naming conventions, and pipeline design
• Partner with BI/reporting teams to ensure data is accurate, performant, and consumable
• Troubleshoot and resolve issues across ingestion, transformation, and storage layers
• Provide technical leadership, mentoring, and best practices in data engineering

Required Qualifications

• 7–10+ years of experience in data engineering or data warehousing
• Advanced SQL expertise across:
  • Oracle
  • SQL Server / Azure SQL
  • Snowflake
• Strong hands-on experience with Azure Data Factory (ADF) (required)
• Advanced SQL query capabilities, including but not limited to: Joins, aggregations, memory tables, CTEs, subqueries (all candidates will be screened for this ability)
• Experience implementing:
  • Incremental data loads
  • UPSERT / MERGE patterns
• Experience integrating data from:
  • Oracle EBS or similarly complex ERP systems
  • REST APIs as data sources
  • Managing orchestrated workflows involving placement of sFTP files
• Strong experience working with:
  • JSON data structures and parsing in SQL
  • Hybrid structured and semi-structured datasets
• Deep understanding of:
  • Dimensional data modeling (star/snowflake schema)
  • Data pipeline architecture and lifecycle

Key Skills

Education

Bachelor's degree