Data Engineer III

sgs-job-6000

Engineering
 California
SQL
Python
Workforce planning
Presto
Trino
Spark SQL
Hive
Data Warehousing
Dataswarm

Contract - 05+ Months

• This role sits in GO Analytics – Global Response Ecosystem, the team that provides trusted data foundations for Client's global operations and response organizations. The contractor will support a mix of high-priority work: (1) workforce measurement – building datasets that track capacity, staffing, and productivity across response teams; (2) response ecosystem reporting – maintaining and improving core reporting used by operations leaders for real-time and weekly decision-making; and (3) pipeline backfill and automation – hardening legacy pipelines, backfilling historical data, and automating manual workflows to improve reliability and self-serve. This backfill + automation work is critical to free up FTE bandwidth for strategic analytics and to provide coverage for an FTE who is on leave.

Job Responsibilities:

  • Partner with data scientists and operations stakeholders to understand data needs and translate them into reliable pipelines and tables; build, maintain, and optimize ETL/ELT pipelines (SQL + Python/Spark) and orchestration schedules; monitor pipeline health, troubleshoot failures, and implement data quality checks and documentation; contribute to data modeling for analytics-ready datasets and support ad-hoc data requests and dashboard backends.

Skills:

  • Advanced SQL (Presto/Trino/Spark SQL) + basic Python for production ETL/ELT — building and optimizing large-scale pipelines over Hive/Spark-based warehouse tables, including data modeling for analytics-ready datasets.
  • Pipeline orchestration and reliability — scheduling and maintaining workflows via Dataswarm (or equivalent), handling backfills, troubleshooting failures, and implementing data quality checks and monitoring.
  • Data warehousing fundamentals at scale — partitioning, incremental loads, performance tuning, and hardening/maintaining legacy pipelines for correctness and SLAs.
  • Dashboard backend experience (Unidash/Tableau or similar) supporting ops reporting.
  • Familiarity with operations/support analytics domain (workforce, capacity, productivity metrics).
  • Version control (Git), code review habits, and documentation discipline.
  • Experience automating manual workflows / building self-serve datasets.
  • Exposure to data quality frameworks, anomaly detection, or SLA alerting.

Education/Experience:

  • Join the Global Response Ecosystem team, where your data engineering work directly powers decisions affecting global operations at Client scale. You'll build reliable, high-impact datasets and pipelines used by operations leaders, own meaningful pieces of the data stack end-to-end, and work with modern tools (SQL, Python, Spark/Presto, Hive, orchestration via Dataswarm/Airflow). Great opportunity to grow production data engineering skills, partner closely with analysts and business stakeholders, and see your work ship to dashboards and decisions quickly.

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