Lead Data Engineer

JPS Tech Solutions; Illinois; On-site; USD 150,000 - 195,000; Full time

Job summary

JPS Tech Solutions seeks a Lead Data Engineer to head enterprise‑level data migration and data quality initiatives as part of SAP ERP transformation programs.

Ideal candidate has deep hands-on experience in extracting, cleansing, transforming, and migrating data from legacy systems such as PeopleSoft, BAAN, and Infor LN into SAP ERP / S4 HANA environments, with strong leadership and collaboration across cross‑functional teams.

Qualifications

• 12+ years of IT experience with data engineering and system architecture.

Responsibilities

• Lead end‑to‑end data conversion and migration activities including scoping, extraction, mapping, transformation, validation, and loading of master and transactional data into SAP systems.

Skills

Leadership

Mentorship

Communication

Analytical thinking

Problem solving

Team collaboration

Independent work

Strategic thinking

Tools

Python

SQL

Spark/PySpark

Azure Data Factory

Azure Synapse

AWS Glue

DataStage

Informatica Data Quality

Talend

Job description

We are looking for a highly experienced Lead Data Engineer to lead enterprise-level data migration and data quality initiatives as part of SAP ERP transformation programs. The ideal candidate will have deep hands‑on experience in data extraction, cleansing, transformation, and migration from legacy systems such as PeopleSoft, BAAN, and Infor LN into SAP ERP / S4 HANA environments.

Key Responsibilities

• Lead end‑to‑end data conversion and migration activities including scoping, extraction, mapping, transformation, validation, and loading of master and transactional data into SAP systems.
• Design and implement data migration solutions to move data from PeopleSoft, BAAN, Infor LN, and other legacy systems to SAP ERP / S4 HANA.
• Define and standardize development, testing, and validation templates for data extraction and conversion.
• Evaluate, select, and implement data extraction, data quality, and cleansing tools.
• Develop and maintain automated ETL/ELT pipelines using Python, Spark/PySpark, SQL, and cloud‑native services.
• Identify and resolve data duplication, integrity, and quality issues; implement preventive governance controls.
• Create and maintain data mapping documents, including mappings to SAP Business Partner (Customer/Supplier) objects.
• Define, monitor, and improve data quality rules, dashboards, and controls.
• Collaborate with data stewards, business owners, architects, and cross‑functional teams to resolve data quality issues.
• Provide technical leadership and mentorship to data engineers and data migration team members.
• Support mock conversions, cutover activities, reconciliation, and post‑migration validation.

Required Qualifications

• 12+ years of overall IT experience, including strong hands‑on experience in data engineering and system architecture.
• 8+ years of experience in data extraction, data migration, data cleansing, and data management.
• Proven experience leading large‑scale data migrations to SAP ERP / S4 HANA.
• Hands‑on experience with SAP HANA and at least one or two SAP implementations.
• Strong programming skills in Python, SQL, PL/SQL, and experience with Spark / PySpark.
• Experience with Azure Data Factory, Azure Functions, Synapse, ADLS and/or AWS Glue and other AWS data services.
• Hands‑on experience with data migration tools such as Syniti or IBM DataStage.
• Experience using data quality tools such as Informatica Data Quality, Talend DQ, or Ataccama.
• Strong understanding of ETL/ELT processes, Master Data Management (MDM), and data governance.
• Excellent analytical, problem‑solving, and communication skills.

Preferred Qualifications

• Experience building and maintaining data quality dashboards and scorecards.
• Experience managing data quality issue trackers and coordinating with data stewards or data owners.
• Strong experience with SQL‑based reporting, Excel, Access, and data analysis tools.
• Familiarity with data warehousing concepts and analytics platforms.
• Experience with data visualization tools.
• Prior experience in a Lead or Architect‑level data engineering role.
• Ability to work independently and lead cross‑functional technical teams.