Principal Data Engineer

1 day ago

Hempstead, NY, United States Worth AI Full time
Principal Data Engineer

Worth AI, a leader in the computer software industry, is looking for a talented and experienced Principal Data Engineer to join their innovative team. At Worth AI, we are on a mission to revolutionize decision-making with the power of artificial intelligence while fostering an environment of collaboration, and adaptability, aiming to make a meaningful impact in the tech landscape. Our team values include extreme ownership, one team and creating raving fans both for our employees and customers.

Worth is looking for a Principal Data Engineer to own the company-wide data architecture and platform. Design and scale reliable batch/streaming pipelines, institute data quality and governance, and enable analytics/ML with secure, cost-efficient systems. Partner with engineering, product, analytics, and security to turn business needs into durable data products.

Responsibilities

What you will do:

  • Architecture & Strategy
    • Define end-to-end data architecture (lake/lakehouse/warehouse, batch/streaming, CDC, metadata).
    • Set standards for schemas, contracts, orchestration, storage layers, and semantic/metrics models.
    • Publish roadmaps, ADRs/RFCs, and "north star" target states; guide build vs. buy decisions.
  • Platform & Pipelines
    • Design and build scalable, observable ELT/ETL and event pipelines.
    • Establish ingestion patterns (CDC, file, API, message bus) and schema-evolution policies.
    • Provide self-service tooling for analysts/scientists (dbt, notebooks, catalogs, feature stores).
    • Ensure workflow reliability (idempotency, retries, backfills, SLAs).
  • Data Quality & Governance
    • Define dataset SLAs/SLOs, freshness, lineage, and data certification tiers.
    • Enforce contracts and validation tests; deploy anomaly detection and incident runbooks.
    • Partner with governance on cataloging, PII handling, retention, and access policies.
  • Reliability, Performance & Cost
    • Lead capacity planning, partitioning/clustering, and query optimization.
    • Introduce SRE-style practices for data (error budgets, postmortems).
    • Drive FinOps for storage/compute; monitor and reduce cost per TB/query/job.
  • Security & Compliance
    • Implement encryption, tokenization, and row/column-level security; manage secrets and audits.
    • Align with SOC 2 and privacy regulations (e.g., GDPR/CCPA; HIPAA if applicable).
  • ML & Analytics Enablement
    • Deliver versioned, documented datasets/features for BI and ML.
    • Operationalize training/serving data flows, drift signals, and feature-store governance.
    • Build and maintain the semantic layer and metrics consistency for experimentation/BI.
  • Leadership & Collaboration
    • Provide technical leadership across squads; mentor senior/staff engineers.
    • Run design reviews and drive consensus on complex trade-offs.
    • Translate business goals into data products with product/analytics leaders.

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