Energy Jobline ZR
Overview
Energy Jobline is the largest and fastest growing global Energy Job Board and Energy Hub. We have an audience reach of over 7 million energy professionals, 400,000+ monthly advertised global energy and engineering jobs, and work with the leading energy companies worldwide. We focus on the Oil & Gas, Renewables, Engineering, Power, and Nuclear markets as well as emerging technologies in EV, Battery, and Fusion. We are committed to ensuring that we offer the most exciting career opportunities from around the world for our jobseekers. 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
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 (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 (IDEAL)
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 If you are interested in applying for this job please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of luck in your next career move.
#J-18808-Ljbffr
Energy Jobline is the largest and fastest growing global Energy Job Board and Energy Hub. We have an audience reach of over 7 million energy professionals, 400,000+ monthly advertised global energy and engineering jobs, and work with the leading energy companies worldwide. We focus on the Oil & Gas, Renewables, Engineering, Power, and Nuclear markets as well as emerging technologies in EV, Battery, and Fusion. We are committed to ensuring that we offer the most exciting career opportunities from around the world for our jobseekers. 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
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 (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 (IDEAL)
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 If you are interested in applying for this job please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of luck in your next career move.
#J-18808-Ljbffr