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Senior Data Engineer (Analytics & Applied AI)

US - Remote (Any location)

Pay
$113,000–188,000/year — pay source
Experience in regulated or government data environments. The annual salary range for this position is $113,000.00-$188,000.00. Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs. What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace.
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Work setting
Remote stated — work setting source
Listed location: US - Remote (Any location)
Read the full posting
Employment
Full-time — employment source
Employment type in the employer’s listing: Full time
From the employer’s posting
Apply at Guidehouse

What you’ll work on

Full posting

We build production data platforms that turn large, complex datasets into reliable analytics and applications.

Data analytics fluency is required — you reason about the numbers, not just move them.

  • You will own systems end to end, make architecture decisions, and drive work forward independently with minimal oversight.

  • Write production Python and build software, not just SQL — services, APIs, tooling, and well-tested, maintainable code.

  • Design and orchestrate cloud data pipelines on AWS with scheduling, retries, data-quality gates, and clean failure handling.

From the employer’s posting
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.
Data analytics fluency is required — you reason about the numbers, not just move them.
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.
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.
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.

What you’ll bring

All qualifications

Core experience

  • Data modeling — dimensional/analytical modeling, grain, SCD, and idempotent recompute patterns.

Preferred experience

  • Experience in regulated or government data environments.
Qualification wording
Data modeling — dimensional/analytical modeling, grain, SCD, and idempotent recompute patterns.
Experience in regulated or government data environments.

Tools in this posting

  • Python
  • SQL
  • AWS
  • DuckDB
  • Iceberg
  • Redshift
  • S3
  • Terraform
  • FastAPI
Source — Tool mentions in context
About the role 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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).

About Guidehouse

Guidehouse is an Equal Opportunity Employer–Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation.

In the employer’s words · Read in context

Posting record

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Actively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier listing.

Status in our records
Live
First seen by us
Oct 21, 2026 · 4 days ago
Recorded sightings
17
Last seen by us
Oct 25, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

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Job description

View original posting ↗

Job Family:

Software Development & Support


Travel Required:

None


Clearance Required:

Ability to Obtain Public Trust

Senior Data Engineer (Analytics & Applied AI)
 

About the role

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.

     

What You Will Need 

  • 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.



The annual salary range for this position is $113,000.00-$188,000.00. Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs.


What We Offer:

Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace.

Benefits include:

  • Medical, Rx, Dental & Vision Insurance

  • Personal and Family Sick Time & Company Paid Holidays

  • Parental Leave

  • 401(k) Retirement Plan

  • Group Term Life and Travel Assistance

  • Voluntary Life and AD&D Insurance

  • Health Savings Account, Health Care & Dependent Care Flexible Spending Accounts

  • Transit and Parking Commuter Benefits

  • Short-Term & Long-Term Disability

  • Tuition Reimbursement, Personal Development, Certifications & Learning Opportunities

  • Employee Referral Program

  • Corporate Sponsored Events & Community Outreach

  • Care.com annual membership

  • Employee Assistance Program

  • Supplemental Benefits via Corestream (Critical Care, Hospital Indemnity, Accident Insurance, Legal Assistance and ID theft protection, etc.)

  • Position may be eligible for a discretionary variable incentive bonus

About Guidehouse

Guidehouse is an Equal Opportunity Employer–Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation.

Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco.

If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1-571-633-1711 or via email at RecruitingAccommodation@guidehouse.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation.

All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or guidehouse@myworkday.com.  Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse.  Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process.

If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse’s Ethics Hotline. If you want to check the validity of correspondence you have received, please contact recruiting@guidehouse.com. Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant’s dealings with unauthorized third parties.

Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.

Source details

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Pay
Experience in regulated or government data environments. The annual salary range for this position is $113,000.00-$188,000.00. Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs. What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace.
Location & working pattern

US - Remote (Any location)

Working pattern and location restrictions need checking in the full posting.

Work authorization

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