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Data Modeler

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Job Description - Data Modeler

  • Set up and run the Data Modeling COE: standards, review
    gates, reusable templates, and knowledge assets.

  • Define and enforce modeling conventions, versioning,
    and operating model (intake → design → review → sign‑off).

  • Drive data governance—cataloging, lineage, policy‑based
    access, encryption/tokenization, and compliance readiness.

  • Lead logical and physical DB design; produce ER
    diagrams and schema diagrams; maintain PTM (physical technology model)
    across RDBMS and NoSQL.

  • Propose and implement re‑structuring of legacy schemas
    for scalability, resiliency, and cost/performance optimization.

  • Architect multi‑tenant strategies (schema/table/row‑level
    isolation) and workload isolation.

  • Define end‑to‑end migration approaches (assessment →
    design → build → cutover → validation) across RDBMS ↔ NoSQL and cloud
    platforms.

  • Orchestrate CDC/ETL/ELT and integrations (e.g., ADF,
    Glue, Kafka/NiFi, Logic Apps, Databricks).

  • Establish reconciliation, golden‑record checks, phased
    cutover plans, and rollback strategies.

  • Lead performance tuning (indexing/partitioning, query
    plan analysis, caching) and Spark optimization to address skew,
    partitioning, and storage formats (Parquet/Delta).

  • Define SLA‑backed observability and capacity planning.
  • Automate repetitive tasks and pipeline scaffolding to
    reduce manual intervention across tech stacks.

  • Implement CI/CD for data pipelines, automated quality
    gates, and IaC for data platforms.



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