Worth AI
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.
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
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
- 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