🚀 Principal Data Engineer

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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 reaving fans both for our employees and customers.

Responsibilities

• 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

Requirements

• 10+ years in data engineering (including 3+ years as staff / principal or equivalent scope)
• Proven leadership of company‑wide data architecture and platform initiatives
• Deep experience with at least one cloud (AWS) and a modern warehouse or lakehouse (e.g., Snowflake, Redshift, Databricks)
• Strong SQL and one programming language (Python or Scala / Java)
• Orchestration (Airflow / Dagster / Prefect), transformations (dbt or equivalent), and streaming (Kafka / Kinesis / PubSub)
• Data modeling (3NF, star, data vault) and semantic / metrics layers
• Data quality testing, lineage, and observability in production environments
• Security best practices: RBAC / ABAC, encryption, key management, auditability

Nice to Have (IDEAL)

• Feature stores and ML data ops; experimentation frameworks
• Cost optimization at scale; multi‑tenant architectures
• Governance tools (DataHub / Collibra / Alation), OpenLineage, and testing frameworks (Great Expectations / Deequ)
• Compliance exposure (SOC 2, GDPR / CCPA; HIPAA / PCI where relevant)
• Model features sourced from complex 3rd‑party data (KYB / KYC, credit bureaus, fraud detection APIs)

Benefits

• Health Care Plan (Medical, Dental & Vision)
• Retirement Plan (401k, IRA)
• Life Insurance
• Unlimited Paid Time Off
• 9 paid Holidays
• Family Leave
• Work From Home
• Free Food & Snacks (Access to Industrious Co‑working Membership!)
• Wellness Resources

Seniority Level

Mid-Senior level

Employment Type

Full‑time

Industries

IT Services and IT Consulting

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