Pay: $80,000–133,000/year — pay source
Previous consulting or client-facing experience. The annual salary range for this position is $80,000.00-$133,000.00. 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 setup: Unconfirmed
Employment: Unconfirmed

What you’ll work on

Design, develop, and maintain scalable data pipelines and ETL/ELT processes supporting analytics, reporting, and operational workloads.
Build and optimize data architectures, data models, and storage solutions across cloud and hybrid environments.
Develop and maintain data engineering solutions using Python, SQL, Spark, and related technologies.

From the employer’s posting

Guidehouse seeks a Senior Data Engineer to design, develop, and optimize modern data platforms, pipelines, and cloud-based analytics solutions. The ideal candidate will have hands-on experience building scalable data ecosystems, strong software engineering fundamentals, and the ability to lead technical efforts while collaborating with multidisciplinary teams to deliver mission-critical data solutions. Design, develop, and maintain scalable data pipelines and ETL/ELT processes supporting analytics, reporting, and operational workloads. Build and optimize data architectures, data models, and storage solutions across cloud and hybrid environments.

Design, develop, and maintain scalable data pipelines and ETL/ELT processes supporting analytics, reporting, and operational workloads. Build and optimize data architectures, data models, and storage solutions across cloud and hybrid environments. Develop and maintain data engineering solutions using Python, SQL, Spark, and related technologies.

Build and optimize data architectures, data models, and storage solutions across cloud and hybrid environments. Develop and maintain data engineering solutions using Python, SQL, Spark, and related technologies. Implement and support cloud-native data platforms leveraging AWS, Azure, Databricks, and other modern technologies.

What you’ll bring

All qualifications

Core experience

Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Data Science, or a related technical field.
Experience in Python, SQL, and data processing frameworks such as Spark or PySpark.
Experience designing, developing, and supporting production-grade data pipelines and ETL/ELT processes.
Experience working with relational and non-relational databases, including data modeling and query optimization.
Experience with cloud platforms such as AWS and/or Azure.
Experience with Databricks, Snowflake, or similar large-scale data processing environments.

Preferred experience

Experience supporting federal, healthcare, public health, or other highly regulated environments.
Familiarity with containerization technologies such as Docker and orchestration platforms such as Kubernetes.
Experience with AWS services such as S3, Redshift, Lambda, ECS, Glue, and SQS.
Ability to independently manage technical tasks and collaborate effectively across teams.

Qualification wording

Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Data Science, or a related technical field.

Experience in Python, SQL, and data processing frameworks such as Spark or PySpark.

Experience designing, developing, and supporting production-grade data pipelines and ETL/ELT processes.

Experience working with relational and non-relational databases, including data modeling and query optimization.

Experience with cloud platforms such as AWS and/or Azure.

Experience with Databricks, Snowflake, or similar large-scale data processing environments.

Experience supporting federal, healthcare, public health, or other highly regulated environments.

Familiarity with containerization technologies such as Docker and orchestration platforms such as Kubernetes.

Experience with AWS services such as S3, Redshift, Lambda, ECS, Glue, and SQS.

Ability to independently manage technical tasks and collaborate effectively across teams.

Tools in this posting

Python
SQL
AWS
Azure
Databricks
Datadog
Docker
Kibana
Redshift
S3
Snowflake
Spark
Terraform
Elasticsearch
Kubernetes
PySpark

Source

- Build and optimize data architectures, data models, and storage solutions across cloud and hybrid environments. - Develop and maintain data engineering solutions using Python, SQL, Spark, and related technologies. - Implement and support cloud-native data platforms leveraging AWS, Azure, Databricks, and other modern technologies.

- THREE (3) or more years in data engineering, software engineering, analytics engineering, or a related discipline. - Experience in Python, SQL, and data processing frameworks such as Spark or PySpark. - Experience designing, developing, and supporting production-grade data pipelines and ETL/ELT processes.

- Develop and maintain data engineering solutions using Python, SQL, Spark, and related technologies. - Implement and support cloud-native data platforms leveraging AWS, Azure, Databricks, and other modern technologies. - Design and implement CI/CD pipelines and DevOps best practices for data engineering workflows.

- Experience working with relational and non-relational databases, including data modeling and query optimization. - Experience with cloud platforms such as AWS and/or Azure. - Experience with Databricks, Snowflake, or similar large-scale data processing environments.

- Familiarity with containerization technologies such as Docker and orchestration platforms such as Kubernetes. - Experience with AWS services such as S3, Redshift, Lambda, ECS, Glue, and SQS. - Strong analytical, troubleshooting, and problem-solving skills.

- Experience with Databricks, Snowflake, or similar large-scale data processing environments. - Experience implementing CI/CD pipelines and version control practices using tools such as Git, GitHub, GitLab, Jenkins, or Azure DevOps. - Experience implementing data quality, monitoring, and operational support processes.

- Excellent verbal and written communication skills. - Experience with Azure services such as Azure Data Factory, Synapse Analytics, Azure Functions, Cosmos DB, and Event Hub. - Familiarity with modern data lakehouse architectures and data governance frameworks.

- Experience with cloud platforms such as AWS and/or Azure. - Experience with Databricks, Snowflake, or similar large-scale data processing environments. - Experience implementing CI/CD pipelines and version control practices using tools such as Git, GitHub, GitLab, Jenkins, or Azure DevOps.

- Experience with monitoring and observability tools such as CloudWatch, Splunk, Kibana, Datadog, or Elasticsearch. - Cloud, Databricks, Snowflake, or related technical certifications. - Experience supporting large-scale data modernization or migration programs.

- Experience implementing Infrastructure-as-Code using Terraform, CloudFormation, or Bicep. - Experience with monitoring and observability tools such as CloudWatch, Splunk, Kibana, Datadog, or Elasticsearch. - Cloud, Databricks, Snowflake, or related technical certifications.

- Experience supporting federal, healthcare, public health, or other highly regulated environments. - Familiarity with containerization technologies such as Docker and orchestration platforms such as Kubernetes. - Experience with AWS services such as S3, Redshift, Lambda, ECS, Glue, and SQS.

- Familiarity with modern data lakehouse architectures and data governance frameworks. - Experience implementing Infrastructure-as-Code using Terraform, CloudFormation, or Bicep. - Experience with monitoring and observability tools such as CloudWatch, Splunk, Kibana, Datadog, or Elasticsearch.

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

Job description

View original posting ↗

Job Family:

Data Science & Analysis

Travel Required:

Up to 10%

Clearance Required:

Ability to Obtain Public Trust

What You Will Do:

Guidehouse seeks a Senior Data Engineer to design, develop, and optimize modern data platforms, pipelines, and cloud-based analytics solutions. The ideal candidate will have hands-on experience building scalable data ecosystems, strong software engineering fundamentals, and the ability to lead technical efforts while collaborating with multidisciplinary teams to deliver mission-critical data solutions.

Design, develop, and maintain scalable data pipelines and ETL/ELT processes supporting analytics, reporting, and operational workloads.
Build and optimize data architectures, data models, and storage solutions across cloud and hybrid environments.
Develop and maintain data engineering solutions using Python, SQL, Spark, and related technologies.
Implement and support cloud-native data platforms leveraging AWS, Azure, Databricks, and other modern technologies.
Design and implement CI/CD pipelines and DevOps best practices for data engineering workflows.
Collaborate with architects, developers, analysts, and business stakeholders to translate requirements into technical solutions.
Lead data integration, migration, and modernization initiatives, including legacy system transformation efforts.
Ensure data quality, integrity, security, and governance standards are incorporated into solution designs.
Monitor, troubleshoot, and optimize data pipelines and production environments to ensure reliability and performance.
Mentor junior data engineers and support technical knowledge sharing across project teams.
Contribute to technical architecture discussions, technology evaluations, and engineering best practices.
Develop and maintain technical documentation including data flows, system designs, deployment procedures, and operational guides.
Role contingent upon contract award.

What You Will Need:

U.S. Citizenship or Green Card is required and must be able to OBTAIN and MAINTAIN a Federal or DHS "PUBLIC TRUST
Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Data Science, or a related technical field.
THREE (3) or more years in data engineering, software engineering, analytics engineering, or a related discipline.
Experience in Python, SQL, and data processing frameworks such as Spark or PySpark.
Experience designing, developing, and supporting production-grade data pipelines and ETL/ELT processes.
Experience working with relational and non-relational databases, including data modeling and query optimization.
Experience with cloud platforms such as AWS and/or Azure.
Experience with Databricks, Snowflake, or similar large-scale data processing environments.
Experience implementing CI/CD pipelines and version control practices using tools such as Git, GitHub, GitLab, Jenkins, or Azure DevOps.
Experience implementing data quality, monitoring, and operational support processes.
Experience working within Agile software development environments.

What Would Be Nice To Have:

Experience supporting federal, healthcare, public health, or other highly regulated environments.
Familiarity with containerization technologies such as Docker and orchestration platforms such as Kubernetes.
Experience with AWS services such as S3, Redshift, Lambda, ECS, Glue, and SQS.
Strong analytical, troubleshooting, and problem-solving skills.
Ability to independently manage technical tasks and collaborate effectively across teams.
Excellent verbal and written communication skills.
Experience with Azure services such as Azure Data Factory, Synapse Analytics, Azure Functions, Cosmos DB, and Event Hub.
Familiarity with modern data lakehouse architectures and data governance frameworks.
Experience implementing Infrastructure-as-Code using Terraform, CloudFormation, or Bicep.
Experience with monitoring and observability tools such as CloudWatch, Splunk, Kibana, Datadog, or Elasticsearch.
Cloud, Databricks, Snowflake, or related technical certifications.
Experience supporting large-scale data modernization or migration programs.
Experience with machine learning data pipelines and AI-enabled solutions.
Previous consulting or client-facing experience.

The annual salary range for this position is $80,000.00-$133,000.00. 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.

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Source & posting history

View original posting ↗

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Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay: Previous consulting or client-facing experience. The annual salary range for this position is $80,000.00-$133,000.00. 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 - TX, San Antonio
- Design, develop, and maintain scalable data pipelines and ETL/ELT processes supporting analytics, reporting, and operational workloads. - Build and optimize data architectures, data models, and storage solutions across cloud and hybrid environments. - Develop and maintain data engineering solutions using Python, SQL, Spark, and related technologies.
Work authorization: What You Will Need: - U.S. Citizenship or Green Card is required and must be able to OBTAIN and MAINTAIN a Federal or DHS "PUBLIC TRUST - Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Data Science, or a related technical field.

Open source at guidehouse.wd1.myworkdayjobs.com ↗Read the full description ↓

Status in our records: Active
First seen by us: Aug 17, 2026
Recorded sightings: 2
Last seen by us: Sep 29, 2026
Employer says posted: Aug 10, 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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