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# Data Engineer III-6377

- **Company:** The Itd
- **Location:** Menlo Park, CA, United States
- **Contract:** Permanent contract
- **Skills:** Query Performance, Airflow, Big Data, Business Process Management, Capability Maturity Model Integration, Code Review, Databases, Computer Engineering, Data Validation, Information Engineering, Data Files, Data Governance, Extract Transform Load (ETL), Data Systems, Data Warehousing, Apache Hive, Python (Programming Language), Software Engineering, SQL Databases, Tableau (Software), Scripting, Sql Optimization, Apache Spark, Git, Information Technology, Data Management, Presto, Tools for Reporting, Software Version Control, Data Pipelines
- **Published:** November 7, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-engineer-iii-6377-menlo-park-ca--73b853e4-c7e5-4a53-8a32-a209ede664c4

## About the Role

Software Engineering, Python Programming/Scripting Language, Automation, International Operations, Data Management, Ecosystems, Data Sets, Database Extract Transform and Load (ETL), Data Quality, SQL (Structured Query Language), * 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., * Bachelor's degree in Computer Science, Computer Engineering, or a related technical field required.

## Description

* 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.