Data Engineer

Job Summary

The Senior Data Warehouse Engineer is responsible for designing, building, and optimizing enterprise data pipelines and data models to transform complex operational data into scalable, consumable datasets. This role will focus on modernizing data from Oracle EBS and other sources into Azure-based platforms, enabling near real-time data availability through incremental load and UPSERT patterns. This role requires deep expertise in Azure Data Factory, strong SQL engineering skills, and experience working with both structured and semi-structured data, including JSON. The engineer will also integrate external data sources via REST APIs and help standardize data for downstream reporting and analytics.

Primary Responsibilities

• 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