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, adaptability, and a commitment to make a meaningful impact in the tech landscape. Our team values include extreme ownership, one team, and creating fans both for our employees and customers.

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 Fin Ops 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

• 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/Pub Sub)
• 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

• Feature stores and ML data ops; experimentation frameworks
• Cost optimization at scale; multi‑tenant architectures
• Governance tools (Data Hub/Collibra/Alation), Open Lineage, 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)

• 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