Principal Data Engineer - Remote Eligible

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.