Senior Data Engineer: Analytics & Applied AI

Guidehouse Inc.; United States; On-site; USD 113,000 - 188,000; Full time

Job summary

Guidehouse Inc. seeks a Senior Data Engineer (Analytics & Applied AI) who writes production-quality Python, designs cloud data pipelines, and ensures numbers are correct. This is a high-autonomy role where you own systems end to end and set technical direction.

You will build data platforms on AWS, implement data-quality gates, and grow into applied AI/ML capabilities, including entity resolution and AI-assisted analytics, with minimal supervision.

Qualifications

• 6+ years in data engineering and/or software engineering for production systems.
• Strong production-quality Python, testing, and CI/CD.
• Expert SQL with window functions and complex joins.
• Hands-on AWS data stack (Glue, S3, Redshift, Lambda, etc.).
• Data modeling and analytical modeling practices.
• Infrastructure as code (Terraform or CDK).
• High autonomy with ownership of systems and architecture.

Responsibilities

• Own data platforms end to end from source ingestion through transformation to analytics and applications with correctness and auditability.
• Write production Python and build services, APIs, and maintainable code.
• Design and orchestrate cloud data pipelines on AWS with scheduling and data-quality gates.
• Model data for analytics and application serving with dimensional modeling and slowly-changing dimensions.
• Implement data-quality checks and reconciliation to defend numbers.
• Drive architecture decisions and adopt AI tooling to accelerate delivery.

Job description

Guidehouse Inc. seeks a Senior Data Engineer (Analytics & Applied AI) who writes production-quality Python, designs cloud data pipelines, and ensures numbers are correct. This is a high-autonomy role where you own systems end to end and set technical direction.

You will build data platforms on AWS, implement data-quality gates, and grow into applied AI/ML capabilities, including entity resolution and AI-assisted analytics, with minimal supervision.