Worth AI is looking for a Principal Data Engineer to own the company-wide data architecture and platform. This role aims to design and scale reliable data pipelines, ensure data quality and governance, and enable analytics and machine learning through secure and cost-efficient systems, ultimately transforming business needs into durable data products.
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.
Responsibilities
- 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.
- 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).
- Define dataset SLAs/SLOs, freshness, lineage, and data certification tiers.
Other
- Proven leadership of company-wide data architecture and platform initiatives.
- 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.
- Compliance exposure (SOC 2, GDPR/CCPA; HIPAA/PCI where relevant).
