Senior Data Engineer - Agile BI & Data Pipelines

CGS Federal (Contact Government Services); San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health, Dental, Vision

Life Insurance

401k

Flexible Spending Account

Paid Time Off

Job summary

CGS Federal (Contact Government Services) is seeking a Data Engineer in San Francisco. You will join the Business Intelligence department to design and implement data pipelines, enabling federal clients with actionable insights.

The role emphasizes an Agile mindset, collaboration with product managers and engineers, and a focus on scalable ETL processes, data quality, and automation. A strong background in Python/SQL and data tools is essential.

Qualifications

• 7+ years of IT experience with large data sets and models.
• Experience building data pipelines from multiple sources.
• Proficiency in ETL, data validation, and testing steps.
• Strong data manipulation skills (Python, R, SQL, SAS).
• Experience with big data storage tools and APIs is a plus.

Responsibilities

• Build end-to-end data pipelines to store and provision data to consumers.
• Contribute as an active Agile/Scrum team member and follow best practices.
• Write code to ensure data extraction and processing performance and reliability.
• Support automation for data ingestion processes.
• Advocate lean-agile engineering and CI/CD practices including automated tests.
• Collaborate across cross-functional teams to document evolving requirements.

Skills

Data pipeline development

Agile/Scrum

Python/SQL/SAS

Data extraction & processing

Data ingest automation

Lean-Agile practices

Cross-functional collaboration

Tools

PostgreSQL

Git

Tableau/Power BI

Job description

CGS Federal (Contact Government Services) is seeking a Data Engineer in San Francisco. You will join the Business Intelligence department to design and implement data pipelines, enabling federal clients with actionable insights.

The role emphasizes an Agile mindset, collaboration with product managers and engineers, and a focus on scalable ETL processes, data quality, and automation. A strong background in Python/SQL and data tools is essential.