Data Engineer III-6377

itD Tech•menlopark,CA, GA

6h•Onsite

About The Position

itD is seeking a Data Engineer III to build, optimize, and maintain scalable data pipelines and analytics-ready datasets that support operational decisions across Meta’s Global Response Ecosystem. The role supports workforce measurement, response ecosystem reporting, pipeline automation, and historical data backfills, helping global operations teams make data-driven decisions. The position is onsite in Menlo Park, California, and is listed for a six-month duration. Pay rate is DOE. Only direct W2 candidates are being considered; sponsorship is not available. The engineer will work with large-scale data engineering systems and collaborate with data scientists, data architects, analysts, and operations stakeholders. The position also includes internal itD practice activities, such as attending community and networking meetings, contributing to thought leadership and Digital Transformation materials, completing case studies and learning content, and working with leadership on career development opportunities.

Requirements

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 in 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.
Bachelor's degree in Computer Science, Computer Engineering, or a related technical field.
Must be a direct W2 candidate; sponsorship is not available.

Nice To Haves

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.

Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines using advanced SQL and Python for large-scale analytics and reporting.
Build, optimize, and maintain data workflows in 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 troubleshooting failures.
Create and maintain analytics-ready datasets and data models for 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 SLAs.
Maintain and improve legacy 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 data solutions and support reporting and dashboard development.
Attend regular internal practice community meetings and internal itD networking events, both in person and virtually.
Collaborate with the itD practice team on industry thought leadership.
Complete client case studies and learning materials, including blogs and media materials.
Build materials that contribute to the Digital Transformation practice.
Work with leadership on career fast-track opportunities.