Senior Data Engineer (Analytics & Applied AI)

Guidehouse•Tysons, VA

2d•$113,000 - $188,000

About The Position

Guidehouse is seeking a Senior Data Engineer to build and operate production data platforms that turn large, complex datasets into reliable analytics and applications. The role combines software engineering and data engineering, requiring production-quality Python, cloud data pipeline design and orchestration, and accountability for the correctness of pipeline outputs. This is a senior, high-autonomy position. The engineer will own systems end to end, make architecture decisions, and drive implementation independently with limited oversight. The role also calls for effective use of agentic coding assistants and the ability to reason about analytics and metrics. Work may expand into applied AI and machine learning, including entity resolution, LLM-assisted analytics, and anomaly or risk scoring. The annual salary range is $113,000 to $188,000. Compensation decisions depend on factors including skills, experience, training, clearances, licensure, certifications, and business needs. The position may be eligible for a discretionary variable incentive bonus. Candidates must obtain approved adjudication of a Federal or DoD public trust before onboarding; active public trust or suitability is preferred.

Requirements

Six or more years of experience in data engineering and/or software engineering building and operating production systems.
University degree and at least six years of relevant prior experience; four years of relevant experience may substitute for formal education.
Strong software engineering skills, including production-quality Python, clean architecture, testing, code review, and CI/CD.
Expert SQL skills, including window functions, complex joins, aggregation-grain reasoning, and query performance.
Hands-on experience with several AWS data and compute services, such as Glue, Step Functions, S3, Redshift, Aurora/RDS, Lambda, EventBridge, ECS/Fargate, and IAM.
Data modeling knowledge, including dimensional and analytical modeling, grain, slowly changing dimensions, and idempotent recompute patterns.
Data-quality discipline, including validating outputs, reconciling totals, and being able to defend reported numbers.
Infrastructure-as-code experience with Terraform or CDK in a real project.
Proven ability to own systems and drive them to completion independently, using sound judgment on architecture and tradeoffs.
Demonstrated effective use of AI coding tools in a real workflow.
Analytics fluency, including profiling datasets, spotting anomalies, reasoning about metrics, and explaining discrepancies.
Ability to obtain and maintain a Federal or DoD public trust; approved adjudication is required before onboarding.

Nice To Haves

Practical applied AI or machine learning experience, such as LLM use (RAG or structured extraction from unstructured text), embeddings, or ML risk scoring; strong interest is also welcomed.
Experience with agent frameworks such as AWS Strands Agents, Bedrock AgentCore, or similar systems for building tool-using or multi-agent systems.
Entity resolution or probabilistic record linkage experience.
API development experience with FastAPI or similar, and enough front-end awareness to collaborate with UI engineers.
Experience with DuckDB, Parquet-based data flows, and data-lake table formats such as Iceberg or Delta.
Experience in regulated or government data environments.
Active public trust or suitability.

Responsibilities

Own data platforms end to end, from source ingestion through transformation to analytics and application layers, prioritizing correctness, idempotency, and auditability.
Write production-quality Python and build services, APIs, tooling, and well-tested, maintainable software.
Design and orchestrate AWS cloud data pipelines with scheduling, retries, data-quality gates, and clean failure handling.
Model data for analytics and application serving, including dimensional and fact modeling, grain decisions, slowly changing dimensions, idempotent recompute patterns, and distinguishing analytical warehouses from application systems of record.
Implement data-quality and reconciliation checks for every pipeline and gate publication on those checks.
Drive architecture and technical decisions independently, evaluate tradeoffs, choose approaches, and lead implementation with limited supervision.
Use agentic coding assistants and AI development tooling to accelerate delivery while maintaining code quality and review discipline.
Contribute to applied AI and machine learning work as it expands, including entity resolution or record linkage, LLM-assisted analytics over structured and unstructured data, and anomaly or risk scoring.

Benefits

Medical, prescription, dental, and vision insurance.
Personal and family sick time and company-paid holidays.
Parental leave.
401(k) retirement plan.
Group term life and travel assistance.
Voluntary life and AD&D insurance.
Health Savings Account and health care and dependent care Flexible Spending Accounts.
Transit and parking commuter benefits.
Short-term and long-term disability.
Tuition reimbursement, personal development, certifications, and learning opportunities.
Employee referral program.
Corporate-sponsored events and community outreach.
Care.com annual membership.
Employee Assistance Program.
Supplemental benefits through Corestream, including critical care, hospital indemnity, accident insurance, legal assistance, and identity theft protection.
Position may be eligible for a discretionary variable incentive bonus.
Flexible benefits package.