Data Engineer Lead

This role is a Data Engineer Lead position for a 6‑month contract, offering $57.05–$60.70 per hour.

Location:

Lisle, IL 60532, United States.

• Lead the data conversion team through scoping, extraction, mapping, and loading of both master data sets and transactional data sets from multiple sources into the SAP system throughout the project phases.
• Design, develop, and implement components to migrate data from legacy platforms to SAP ERP platforms.
• Define development and test templates and methods for extracting data from various sources, with a strong emphasis on People Soft, BAAN, and Infor LN systems.
• Evaluate and select appropriate tools and technologies for data extraction and cleansing.
• Write programs and scripts to automate data extraction, cleansing, transformation, and load processes.
• Identify and resolve data duplication issues; perform data cleansing to ensure the accuracy and quality of data and participate in governance for preventive measures at source.
• Create and maintain data mapping documents to map source data attributes to Business Partner (customer/supplier) attributes.
• Monitor data quality issues and refine data quality rules and checks as needed.
• Collaborate with cross‑functional teams, technology, and architecture groups to understand data requirements and implement data‑centric solutions.
• Document processes, methodologies, and best practices for data extraction and cleansing.
• Continuously improve data management processes and monitor data quality.

• 5+ years of overall technology experience that includes at least 4+ years of hands‑on software development, data engineering, and systems architecture.
• Experience deploying modern data solutions leveraging components such as Azure functions, Azure Data Factory, or AWS Glue.
• Experience with data migration platforms like Syniti or Data Stage.
• Experience with at least one data quality product (e.g., Informatica Data Quality, Talend DQ, or Atacama).
• Experience implementing SAP ERP solutions (at least one or two implementations) and hands‑on experience with SAP HANA.

• Proven experience in data extraction, data cleansing, and data management.
• Strong proficiency in Python, Spark, PySpark, PLSQL, Pandas, or similar.
• Hands‑on experience with Syniti, Azure Data Factory, Synapse, ADLS, or AWS Glue and other AWS data services.
• Design, develop, optimize, and maintain data pipelines in Azure or AWS cloud platforms.
• Thorough understanding of data quality, master data management concepts, and ETL/ELT operations.
• Solid experience developing and maintaining data quality dashboards.
• Solid experience maintaining a data quality issue tracker and following up with data stewards or owners to resolve critical issues.
• Strong background in data analysis, including planning and execution of data cleansing and complex conversions.
• Ability to develop reports and analyze, parse, and manipulate data using SQL and tools such as Excel, Access, and SQL Loader.
• Strong problem‑solving skills and attention to detail.
• Ability to work independently and as part of a team.
• Excellent communication and documentation skills.
• Experience with data visualization tools and techniques; familiarity with data warehousing processes.
• Knowledge of data governance and data quality best practices.

Job Type: Contract – 40 hours per week, flexible schedule.