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Data Engineer- Python, AI​/ML

Job in Troy, Oakland County, Michigan, 48083, USA
Listing for: Motion Recruitment
Full Time position
Listed on 2026-05-24
Job specializations:
  • IT/Tech
    Data Engineer, Data Analyst, Data Scientist, Data Science Manager
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below
  • Build and maintain Python and SQL pipelines for governance-related ingestion, cleaning, transformation, and validation of structured and semi-structured data.
  • Implement and operate data quality checks, schema validation, and integrity rules across pipelines; investigate and resolve quality issues.
  • Contribute to master data workflows: standardization, deduplication, and consolidation of data from heterogeneous sources into consistent reference and golden-record datasets.
  • Instrument pipelines for data lineage, metadata, and catalog tooling.
  • Develop pipelines that feed governance dashboards and reporting in Tableau, Power BI, or Looker.
  • Build reproducible, well-documented pipelines for compliance and audit reporting.
  • Contribute to AI / ML-assisted governance use cases: embedding-based data classification, anomaly detection on quality metrics, LLM-assisted catalog search, and MCP-based exposure of governed datasets to AI assistants.
  • Partner with team leads, data stewards, and stakeholders to translate governance requirements into engineering work.
  • Follow team engineering practices:
    Git, code review, modular pipeline design, automated testing, CI/CD.
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Statistics, or a related field.
  • 2+ years building data pipelines in Python (Pandas, Num Py, Sci Py) and SQL.
  • Working experience with Apache Spark or PySpark and workflow orchestration (Apache Airflow).
  • Schema design across relational (Postgre

    SQL, MySQL, SQL Server) and analytical databases, including standardization across heterogeneous sources.
  • Experience implementing data quality validation, EDA, and integrity enforcement on production datasets.
  • Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP).
  • Working familiarity with Python ML libraries (Scikit-Learn) for feature engineering and exploratory analysis.
  • Experience producing analytics-ready datasets for BI tools (Tableau, Power BI, or Looker).
  • Git, code review, and CI/CD practices.
  • Clear technical communication and collaborative working style.
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