Jobs via Dice

Lead Data Engineer -W2 Contract

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Lead Data Engineer on a W2 contract, requiring 6+ years of IT experience, including 4+ in data engineering. Key skills include SAP ERP, Azure Data Factory, data migration, and strong SQL proficiency. Local candidates preferred.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 13, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Lisle, IL
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🧠 - Skills detailed
#Azure Data Factory #Data Migration #AWS Glue #Data Extraction #SAP Hana #Python #Data Engineering #Visualization #Documentation #Automation #Pandas #Informatica IDQ (Informatica Data Quality) #Spark (Apache Spark) #MDM (Master Data Management) #PeopleSoft #PySpark #ADLS (Azure Data Lake Storage) #SQL (Structured Query Language) #Informatica #Data Pipeline #Cloud #Data Mapping #ADF (Azure Data Factory) #AWS (Amazon Web Services) #Data Quality #Migration #SAP #"ETL (Extract #Transform #Load)" #Data Cleansing #Data Management #Synapse #Talend #Data Governance #Data Conversion #DataStage #Azure
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, JKV International, is seeking the following. Apply via Dice today! Note: Local candidates preferred. Job Description As a Data Engineer Lead, you will play a critical role in ensuring the accuracy, reliability, and usability of enterprise data. You will lead data conversion and migration efforts, select appropriate tools, perform technical data extraction, write automation programs, and manage data from multiple legacy systems including PeopleSoft, BAAN, and Infor LN. You will work closely with cross-functional teams to migrate and cleanse data for SAP ERP implementations, enabling high-quality analytics and data-driven business decisions. Key Responsibilities • Lead the data conversion team through scoping, extraction, mapping, and loading of master and transactional data into SAP systems across project phases • Design, develop, and implement data migration components from legacy platforms to SAP ERP (S/4 HANA) • Define extraction and testing templates and methodologies for multiple source systems, with strong focus on PeopleSoft, BAAN, and Infor LN • Evaluate and select appropriate tools and technologies for data extraction, cleansing, and migration • Develop programs and scripts to automate ETL/ELT processes • Identify, analyze, and resolve data duplication and data quality issues • Perform data cleansing and participate in data governance and preventive controls • Create and maintain detailed data mapping documents (source to SAP Business Partner/customer/supplier attributes) • Monitor data quality metrics and continuously refine quality rules and validations • Collaborate with technology, architecture, and business teams to implement data-centric solutions • Document processes, standards, methodologies, and best practices Minimum Requirements • 6+ years of overall IT experience, including 4+ years in data engineering / software development / systems architecture • Experience deploying modern data solutions using Azure Functions, Azure Data Factory, or AWS Glue • Hands-on experience with data migration platforms such as Syniti or IBM DataStage • Experience with data quality tools (Informatica Data Quality, Talend DQ, Atacama, etc.) • Experience with SAP ERP implementations (at least 1–2 projects) • Hands-on experience with SAP HANA Preferred Qualifications • Strong experience in data extraction, data cleansing, and data management • Proficiency in Python, Spark, PySpark, PL/SQL, Pandas or similar technologies • Hands-on experience with Syniti, Azure Data Factory, Synapse, ADLS, AWS Glue, and other cloud data services • Experience designing, optimizing, and maintaining cloud-based data pipelines (Azure/AWS) • Strong understanding of data quality, master data management (MDM), and ETL/ELT concepts • Experience developing data quality dashboards and managing data quality issue trackers • Strong SQL skills and experience with Excel, Access, SQL Loader, and reporting tools • Strong analytical, problem-solving, and attention-to-detail skills • Excellent communication and documentation skills • Familiarity with data visualization, data warehousing, and data governance best practices