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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer (Analytics & Applied AI) - **Company:** Guidehouse Inc. - **Location:** Tysons, VA, United States - **Experience:** Expert - **Salary:** $113,000.0 - $188,000.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Query Performance, Multitier Architecture, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Data Analysis, Application Layers, Software Applications, Audit Trail, Big Data, Cloud Database, Code Review, Continuous Integration, Information Engineering, Data Files, Identity and Access Management, Information Extraction, Python (Programming Language), Operational Databases, Server Administration, Software Engineering, SQL Databases, Data Streaming, Unstructured Data, Parquet, Scripting, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, AgentCore, AI Coding Agents, Agentic-AI, Fastapi, Data Analytics, Maintaining Code, AWS Fargate, AWS Data Analytics, Data Management, Api Design, Entity Resolution, Terraform - **Published:** October 27, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-data-engineer-analytics-applied-ai-tysons-va--21c6c89c-cffa-4892-acef-fbcae1fc749a ## About the Role Artificial Intelligence (AI), Data Analysis, Software Development, Software Administration, Willing to Travel, Artificial Intelligence (AI), Data Analysis, Software Engineering, Python Programming/Scripting Language, Data Sets, * SIX (6+) years in data engineering and/or software engineering building and operating production systems. * University Degree and minimum SIX (6) years of prior relevant experience; FOUR (4) years of relevant experience may be substituted for formal education. * Strong software engineering - production-quality Python, clean architecture, testing, code review, and CI/CD. You build software, not just scripts. * Expert SQL - window functions, complex joins, aggregation-grain reasoning, and query performance. * AWS data & compute stack - hands-on with several of: Glue, Step Functions, S3, Redshift, Aurora/RDS, Lambda, EventBridge, ECS/Fargate, IAM. * Data modeling - dimensional/analytical modeling, grain, SCD, and idempotent recompute patterns. * Data-quality discipline - you validate outputs, reconcile totals, and defend your numbers. * Infrastructure as code - Terraform or CDK in a real project. * High autonomy - proven ability to own systems and drive them to completion independently, with sound judgment on architecture and tradeoffs. * Agentic coding assistants - demonstrated, effective use of AI coding tools in a real workflow. * Analytics fluency - profile a dataset, spot anomalies, reason about what a metric means, and explain discrepancies. * Must be able to obtain and maintain a Federal or DoD "public trust"; candidates must obtain approved adjudication of their public trust prior to onboarding with Guidehouse. Candidates with an active public trust or suitability are preferred What Would Be Nice to Have * Applied AI / ML - practical LLM use (RAG, structured extraction from unstructured text), embeddings, or ML risk-scoring; strong interest counts even without deep production experience. * Agent frameworks - AWS Strands Agents, Bedrock AgentCore, or similar for building tool-using / multi-agent systems. * Entity resolution / record linkage - probabilistic matching * API development - FastAPI or similar; enough front-end awareness to collaborate with UI engineers. * DuckDB / Parquet-based data flows and data-lake table formats (Iceberg/Delta). * Experience in regulated or government data environments. ## Description We build production data platforms that turn large, complex datasets into reliable analytics and applications. We are looking for a Senior Data Engineer who is equally strong as a software engineer and a data engineer - someone who writes production-quality Python, designs and orchestrates cloud data pipelines, and stands behind the correctness of the numbers those pipelines produce. This is a senior, high-autonomy role. You will own systems end to end, make architecture decisions, and drive work forward independently with minimal oversight. You should be comfortable setting technical direction, not just executing tickets. Experience with agentic coding assistants (using AI tooling to move faster while keeping quality high) is expected - we build with modern tooling and want engineers who leverage it well. Data analytics fluency is required - you reason about the numbers, not just move them. What you'll do * Own data platforms end to end - from source ingestion through transformation to the analytics and application layers that consume them - with correctness, idempotency, and auditability as first-class requirements. * Write production Python and build software, not just SQL - services, APIs, tooling, and well-tested, maintainable code. This is a software-engineering role as much as a data role. * Design and orchestrate cloud data pipelines on AWS with scheduling, retries, data-quality gates, and clean failure handling. * Model data for analytics and application serving - dimensional/fact modeling, grain decisions, slowly-changing dimensions, idempotent recompute patterns, and the distinction between an analytical warehouse and an application system-of-record. * Implement data-quality and reconciliation checks that run every pipeline and gate publication - you don't ship numbers you can't defend. * Drive architecture and technical decisions independently - evaluate tradeoffs, choose approaches, and lead implementation with limited supervision. * Use agentic coding assistants effectively - leverage AI development tooling to accelerate delivery while maintaining code quality and review discipline. * Grow into applied AI/ML - entity resolution / record linkage, LLM-assisted analytics over structured and unstructured data, and anomaly/risk scoring as the work expands.