Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Menlo Park, CA, United States
Posted
21 hours ago
SQLGitApache SparkETLTableauHivePythonData AnalysisSharePointITIL
Job Description
Start/End Dates: 11/30/2026 - 5/14/2027
Tax Work Location: US - CA - Menlo Park
Job Title: Data Analytics & Engineering - Data Engineer III
Must have skills:
1) 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
2) Pipeline orchestration and reliability — scheduling and maintaining workflows via Dataswarm (or equivalent), handling backfills, troubleshooting failures, and implementing data quality checks and monitoring
3) Data warehousing fundamentals at scale — partitioning, incremental loads, performance tuning, and hardening/maintaining legacy pipelines for correctness and SLAs
Nice to have:
1) Dashboard backend experience (Unidash/Tableau or similar) supporting ops reporting
2) Familiarity with operations/support analytics domain (workforce, capacity, productivity metrics)
Version control (Git), code review habits, and documentation discipline
3) Experience automating manual workflows / building self-serve datasets
Exposure to data quality frameworks, anomaly detection, or SLA alerting
Job Description: Summary:
The main function of the Data Engineer is to develop, evaluate, test and maintain architectures and data solutions within our organization. The typical Data Engineer executes plans, policies, and practices that control, protect, deliver, and enhance the value of the organization's data assets.
Job Responsibilities:
• Design, construct, install, test and maintain highly scalable data management systems.
• Ensure systems meet business requirements and industry practices.
• Design, implement, automate and maintain large scale enterprise data ETL processes.
• Build high-performance algorithms, prototypes, predictive models and proof of concepts.
Skills:
• Ability to work as part of a team, as well as work independently or with minimal direction.
• Excellent written, presentation, and verbal communication skills.
• Collaborate with data architects, modelers and IT team members on project goals.
• Strong PC skills including knowledge of Microsoft SharePoint.
Education/Experience:
• Bachelor's degree in a technical field such as computer science, computer engineering or related field required.
• Process certification, such as, Six Sigma, CBPP, BPM, ISO 20000, ITIL, CMMI.
Tax Work Location: US - CA - Menlo Park
Job Title: Data Analytics & Engineering - Data Engineer III
Must have skills:
1) 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
2) Pipeline orchestration and reliability — scheduling and maintaining workflows via Dataswarm (or equivalent), handling backfills, troubleshooting failures, and implementing data quality checks and monitoring
3) Data warehousing fundamentals at scale — partitioning, incremental loads, performance tuning, and hardening/maintaining legacy pipelines for correctness and SLAs
Nice to have:
1) Dashboard backend experience (Unidash/Tableau or similar) supporting ops reporting
2) Familiarity with operations/support analytics domain (workforce, capacity, productivity metrics)
Version control (Git), code review habits, and documentation discipline
3) Experience automating manual workflows / building self-serve datasets
Exposure to data quality frameworks, anomaly detection, or SLA alerting
Job Description: Summary:
The main function of the Data Engineer is to develop, evaluate, test and maintain architectures and data solutions within our organization. The typical Data Engineer executes plans, policies, and practices that control, protect, deliver, and enhance the value of the organization's data assets.
Job Responsibilities:
• Design, construct, install, test and maintain highly scalable data management systems.
• Ensure systems meet business requirements and industry practices.
• Design, implement, automate and maintain large scale enterprise data ETL processes.
• Build high-performance algorithms, prototypes, predictive models and proof of concepts.
Skills:
• Ability to work as part of a team, as well as work independently or with minimal direction.
• Excellent written, presentation, and verbal communication skills.
• Collaborate with data architects, modelers and IT team members on project goals.
• Strong PC skills including knowledge of Microsoft SharePoint.
Education/Experience:
• Bachelor's degree in a technical field such as computer science, computer engineering or related field required.
• Process certification, such as, Six Sigma, CBPP, BPM, ISO 20000, ITIL, CMMI.
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