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Data Engineer - Data Engineer II
Data Engineer - Data Engineer IISeattle Staffing • Seattle, WA, United States
Data Engineer - Data Engineer II

Data Engineer - Data Engineer II

Seattle Staffing • Seattle, WA, United States
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Data Engineer II

Our mission is to eliminate operational bottlenecks through automation and AI, creating the technical foundation that enables breakthrough sustainability innovations essential for net zero.

Responsibilities :

  • Working with business-critical sustainability data pipelines.
  • Migrating production ETL jobs from legacy data platforms to modern infrastructure.
  • Setting up workflow orchestration platforms in new accounts.
  • Translating existing data workflows into scalable pipelines.
  • Implementing robust validation to ensure data consistency and quality throughout the migration.
  • Working across multiple critical data domains including sales data, active device telemetry, transportation carbon emissions, energy consumption metrics, sustainability badging workflows, and executive reporting dashboards.
  • Partnering with Science team members and program teams who depend on these pipelines for daily operations.
  • Coordinating with upstream data owners to secure access permissions, collaborating with platform teams to troubleshoot integration issues, and communicating migration progress and risks to stakeholders across the organization.
  • Responsible for comprehensive documentation of the new architecture, including data lineage, dependencies, monitoring strategies, and operational runbooks.
  • Implementing data quality checks and alerting to proactively identify issues before they impact downstream consumers.

Required Skills & Experience :

  • 3-6 years building and maintaining production data pipelines in complex enterprise environments.
  • Strong SQL skills for writing complex transformations, optimizing query performance, and troubleshooting data quality issues across large datasets.
  • Hands-on experience with AWS data services including Redshift, S3, Glue, and IAM for data access management.
  • Deep understanding of ETL best practices including data validation, error handling, idempotency, and lineage tracking.
  • Experience with Python or Spark for implementing data transformation logic.
  • Strong analytical skills and ability to work with large, complex datasets spanning multiple source systems.
  • Excellent communication and stakeholder management skills, with ability to coordinate across multiple technical teams and translate technical concepts for non-technical audiences.
  • Ability to partner directly with technical stakeholders to understand requirements and deliver solutions that meet operational needs.
  • Proven track record managing data migrations or large-scale infrastructure transitions with minimal business disruption.
  • Preferred Qualifications :

  • Experience with workflow orchestration platforms.
  • QuickSight experience for dashboard development.
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