Principal Data Engineer

Job Description

Job Description

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.

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.

Requirements

Nice to Have

Benefits