Data Engineer 3

Data Engineer III

itD is seeking a Data Engineer III to build, optimize, and maintain scalable data pipelines and analytics-ready datasets that power critical operational decisions across Meta’s Global Response Ecosystem. This role will support workforce measurement, response ecosystem reporting, pipeline automation, and historical data backfills, helping global operations teams make informed, data-driven decisions. The ideal candidate will bring strong expertise in SQL, Python, large-scale data engineering, and pipeline orchestration, with a proven ability to develop reliable ETL/ELT workflows and maintain high-quality data infrastructure.

Location: Onsite – Menlo Park, California (CA), United States.

Pay Rate: DOE

Duration: 6 Months
We provide comprehensive medical benefits, a 401k plan, paid holidays, and more.
Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship.

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Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using advanced SQL and Python to support large-scale analytics and reporting requirements.
• Build, optimize, and maintain data workflows across Hive/Spark-based data warehouse environments, ensuring performance, accuracy, and reliability.
• Develop and manage pipeline orchestration workflows using Dataswarm, Airflow, or equivalent tools, including scheduling, backfills, and failure troubleshooting.
• Create and maintain analytics-ready datasets and data models supporting workforce measurement, staffing, capacity, and productivity reporting.
• Monitor pipeline health, implement data quality checks, and establish monitoring practices to ensure data accuracy and adherence to service-level agreements (SLAs).
• Maintain and improve legacy data pipelines, automate manual workflows, and develop self-service datasets to improve operational efficiency.
• Partner with data scientists, data architects, analysts, and operations stakeholders to translate business requirements into reliable data solutions and support reporting and dashboard development.

Internal Responsibilities

• Attend regular internal practice community meetings.
• Collaborate with your itD practice team on industry thought leadership.
• Complete client case studies and learning material (blogs, media material).
• Build out material to contribute to the Digital Transformation practice.
• Attend internal itD networking events (in person and virtual).
• Work with leadership on career fast-track opportunities.

Required Qualifications and Skills

• Strong proficiency in advanced SQL, including Presto, Trino, or Spark SQL.
• Basic to intermediate Python programming experience for production ETL/ELT development.
• Experience building, optimizing, and maintaining large-scale data pipelines across Hive/Spark-based data warehouse environments.
• Strong understanding of data warehousing fundamentals, including partitioning, incremental loads, data modeling, and query performance optimization.
• Experience with pipeline orchestration tools such as Dataswarm, Airflow, or equivalent platforms.
• Experience troubleshooting pipeline failures, managing historical backfills, implementing data quality checks, and maintaining reliable workflows.
• Understanding of data pipeline monitoring, reliability, and SLA requirements.

Preferred Qualifications and Skills

• Experience supporting dashboard backends using Unidash, Tableau, or similar reporting platforms.
• Familiarity with operations and support analytics, including workforce, capacity, staffing, and productivity metrics.
• Experience with Git, version control, code reviews, and technical documentation.
• Experience automating manual workflows and building self-service datasets.
• Exposure to data quality frameworks, anomaly detection, and SLA alerting.
• Experience working with data scientists, analysts, and business stakeholders in large-scale data environments.
• Familiarity with data engineering process certifications such as Six Sigma, CBPP, BPM, ISO 20000, ITIL, or CMMI.

Education

• Bachelor's degree in Computer Science, Computer Engineering, or a related technical field required.