Data Engineer

Description

We are looking for a Data Engineer to join a Contract engagement supporting people analytics and HR-focused data initiatives in Philadelphia, Pennsylvania.

This role is centered on designing, building, and refining scalable data pipelines and curated data assets using Azure Databricks and Azure Data Factory.

The ideal candidate will be comfortable working hands-on with complex source data, translating business needs into reliable transformations, and delivering production-ready solutions with minimal oversight.

Responsibilities

• Design, build, and maintain robust ETL and ELT workflows that support HR and workforce data products.
• Develop scalable data transformations using Python, SQL, Spark, and Azure Databricks to prepare high-quality datasets for downstream use.
• Orchestrate and monitor pipeline execution through Azure Data Factory to ensure dependable and timely data delivery.
• Analyze existing source systems and data structures to map requirements and create efficient ingestion and transformation logic.
• Partner with stakeholders across HR and analytics teams to turn business questions into practical engineering solutions.
• Improve data quality, performance, and reliability by applying modern engineering standards, testing practices, and documentation.
• Support integrations across HRIS and related platforms, including contributing to interface development where needed.
• Create production-ready datasets that enable reporting, workforce analysis, and broader people data initiatives.

Requirements

• Proven experience working as a Data Engineer in hands-on pipeline development roles.
• Strong proficiency in Python, SQL, Spark SQL, and ETL development.
• Deep experience with Databricks, including Azure Databricks, for large-scale data processing.
• Practical expertise with Azure Data Factory for pipeline orchestration and workflow management.
• Familiarity with HRIS platforms, HR data domains, and workforce-related reporting concepts.
• Ability to quickly assess unfamiliar data sources and independently deliver production-quality solutions.
• Understanding of modern data engineering practices, including performance optimization, testing, and maintainable design.
• Experience with Infor data models or interfaces, and Power BI dashboard development, is advantageous but not required.

Technology Doesn't Change the World, People Do.