Data Engineer III

Title: Data Engineer III
Duration: 6-month contract with possible extension
Location: Menlo Park, CA - Onsite
Pay rate: $95-$97.90/hr. on W2
 
We are seeking an experienced Data Engineer to design, build, and maintain scalable data pipelines and analytics-ready datasets that support business operations and decision-making. This role requires expertise in large-scale data processing, ETL/ELT development, data warehousing, and workflow orchestration.
 
Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines and data workflows.
• Build and optimize analytics-ready datasets for reporting and operational insights.
• Develop solutions using SQL, Python, Spark, Hive, and related big data technologies.
• Maintain and monitor production data pipelines, troubleshoot failures, and implement preventive measures.
• Perform data backfills, workflow automation, and data quality validation.
• Collaborate with analysts, data scientists, and business stakeholders to understand requirements and deliver trusted data solutions.
• Support reporting platforms and dashboard backend datasets.
• Optimize data warehouse performance through partitioning, incremental processing, and tuning techniques.
• Create documentation and follow best practices for code quality, reliability, and scalability.

 
Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field.
• 5+ years of Data Engineering experience.
• Strong expertise in:
  • SQL (Presto, Trino, Spark SQL, or similar)
  • Python
  • Spark and Hive
  • ETL/ELT pipeline development
  • Data warehousing and data modeling
  • Workflow orchestration tools such as Airflow, Dataswarm, or equivalent
• Experience with data quality monitoring, pipeline reliability, and production support.

 
Preferred Qualifications

• Experience supporting dashboard and reporting solutions using Tableau, Unidash, or similar BI tools.
• Familiarity with workforce, operations, or productivity analytics.
• Experience with Git, code reviews, and software development best practices.
• Knowledge of data quality frameworks, SLA monitoring, and automation solutions.

 

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