Data Engineers (Principal and Senior roles)
Worth AI
Posted: November 13, 2025
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Quick Summary
A Principal Data Engineer at Worth AI must be an expert in data engineering, with a proven track record of delivering high-quality solutions and collaborating with cross-functional teams to drive data-driven decision-making.
Required Skills
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 Senior and Principal level Data Engineers 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:
• 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.
** All Remote Hires - will be required to travel to Orlando, Florida at least twice per year for Town Halls and team collaboration in addition to orientation in Orlando, Florida.
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