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Data Engineer; Data Product

Job in Warsaw, Kosciusko County, Indiana, 46580, USA
Listing for: TechDigital Group
Full Time position
Listed on 2026-05-13
Job specializations:
  • IT/Tech
    Data Engineer, Data Analyst, Data Science Manager
  • Engineering
    Data Engineer, Data Science Manager
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Data Engineer (Data Product)

Mandatory Skills

  • Strong understanding of Data as a Product mindset
  • Ability to convert business outcomes into data product requirements
  • Defining and managing Data product scope/Data contracts
  • Domain knowledge (e.g., Finance, Sales, Supply Chain, Customer, Risk)
  • Expert in ETL / ELT design patterns
  • Hands on experience with Azure / AWS / GCP
  • Hands on experience with Data Warehouses (Snowflake/Azure Synapse)
Data Product Engineering Ownership
  • Lead the design, build, and maintenance of domain owned data products
  • Translate product requirements into scalable data engineering solutions
  • Ensure data products meet defined:
    • Functional requirements
    • SLAs / SLOs
    • Quality and compliance standards
Collaboration with Data Product Owner
  • Partner closely with the Data Product Owner to:
    • Understand business outcomes and priorities
    • Refine data product scope and roadmap
    • Balance delivery speed with technical sustainability
  • Provide technical input for backlog prioritization and sprint planning
Data Pipeline & Transformation Design
  • Design and implement ETL/ELT pipelines for data products
  • Support:
    • Batch and near real time processing
    • Structured and semi structured data
  • Manage schema evolution and backward compatibility
  • Implement data contracts for product consumers
Data Quality, Reliability & Trust
  • Define and enforce data quality rules for data products
  • Implement:
    • Validation checks
    • Reconciliation logic
    • Data freshness monitoring
  • Ensure high availability and fault tolerance
  • Lead root cause analysis for data incidents
  • Drive continuous quality improvement
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