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Data Engineer Sr; DBT

Job in Butlerville, Jennings County, Indiana, 47223, USA
Listing for: NTT DATA, Inc.
Full Time position
Listed on 2026-10-18
Job specializations:
  • IT/Tech
    Data Engineering, Information Security & Data Protection, Data Analyst, Data Warehousing
Salary/Wage Range or Industry Benchmark: 150000 - 190000 USD Yearly USD 150000.00 190000.00 YEAR
Job Description & How to Apply Below
Position: Data Engineer Sr (DBT)
Location: Butlerville

Roles & Responsibilities
  • Design and implement staging, core, and mart layers using standard dbt patterns and folder structures.
  • Develop and maintain dbt tests (schema tests, data tests, custom tests) to ensure data quality and integrity.
  • Implement snapshots, seeds, macros, and reusable components where appropriate.
  • Collaborate with Snowflake developers to ensure physical data structures support dbt models efficiently.
  • Work with functional teams to ensure functional equivalence between legacy Informatica outputs and new dbt outputs.
  • Participate in performance tuning of dbt models and Snowflake queries.
  • Integrate dbt with CI/CD pipelines (e.g., Azure Dev Ops, Git Hub Actions) for automated runs and validations.
  • Contribute to documentation of dbt models, data lineage, and business rules.
  • Participate in defect analysis, bug fixes, and enhancements during migration and stabilization phases.
Experience
  • 10+ years in modern ELT / transformation engineering, with strong expertise in DBT-based development for curated enterprise data layers.
  • Experience defining DBT project standards, modular model design, testing frameworks, documentation, macros, environment strategy, and deployment controls.
  • Proven ability to lead development of conformed Silver layer models across Policy, Claims, Billing, and shared dimensions / reference domains.
  • Strong experience integrating DBT with Databricks / Delta Lake, orchestration tools, version control, and automated quality checks.
  • Able to guide developer productivity, code review standards, reusability, performance tuning, and traceability from mapping to model implementation.
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