Data Engineer

Guidehouse•San Antonio, TX

8h•Onsite

About The Position

As a Manager in Guidehouse’s AI & Data practice, you will serve as a hands-on technical leader and delivery manager designing and implementing modern cloud-native data platforms for federal clients, with a primary emphasis on AWS and Databricks. You will lead architecture decisions, mentor engineers, and ensure high-quality, secure, and scalable delivery aligned to mission outcomes.

Requirements

US Citizenship required.
An ACTIVE and MAINTAINED "SECRET" Federal or DoD security clearance.
Bachelor’s degree obtained or equivalent experience.
Seven (7+) years of progressive experience in data engineering, data platform delivery, or data architecture roles, including leading technical teams or workstreams.
Strong hands-on experience with AWS data platforms, including designing and operating production systems leveraging Databricks on AWS.
Deep expertise with Apache Spark, Databricks, Delta Lake, Python, and SQL, including performance tuning of distributed workloads.
Experience designing scalable, secure data architectures that support analytics, reporting, and advanced use cases (e.g., AI/ML enablement).
Familiarity with Agile delivery methods and proven ability to collaborate effectively with cross-functional and client teams.
Strong written and verbal communication skills, including the ability to explain complex technical topics to non-technical stakeholders.

Nice To Haves

Experience delivering Azure-based data platforms, including Azure Databricks, ADLS Gen2, Azure Data Factory, or Synapse Analytics.
Bachelor’s degree obtained. Computer Science, Engineering, Information Systems, or a related technical field.
Experience with Databricks Unity Catalog, including permissions management and governance enablement.
Infrastructure-as-Code experience (e.g., Terraform) and advanced CI/CD automation for data platforms.
Experience with streaming and event-driven architectures (e.g., Kafka, Kinesis).
Cloud or platform certifications (AWS, Databricks, or Azure).
Prior experience supporting DoD or Defense & Security federal clients.

Responsibilities

Architect and lead delivery of AWS-based lakehouse solutions using Databricks, including integration with AWS-native services such as S3, Glue, Lambda, IAM, and Redshift where appropriate.
Design, build, and optimize ETL/ELT pipelines leveraging Databricks, Apache Spark, Delta Lake, Python, and SQL, supporting batch and streaming use cases.
Define and enforce data architecture standards including ingestion patterns, layered/medallion designs, schema evolution, performance tuning, and cost optimization.
Implement production-grade engineering practices, including data quality validation, reconciliation, logging, monitoring, and operational alerting.
Apply data security and governance controls appropriate for federal and defense environments, including role-based access, controlled data handling, and auditability.
Partner with client stakeholders and product owners to translate mission and business requirements into technical designs, delivery roadmaps, and implementation plans.
Lead and mentor data engineers through code reviews, architecture reviews, and delivery execution; contribute to reusable accelerators and reference architectures.
Establish and mature CI/CD pipelines for Databricks workloads and supporting infrastructure, improving reliability, repeatability, and compliance of releases.

Benefits

Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Parental Leave and Adoption Assistance
401(k) Retirement Plan
Basic Life & Supplemental Life
Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
Short-Term & Long-Term Disability
Student Loan PayDown
Tuition Reimbursement, Personal Development & Learning Opportunities
Skills Development & Certifications
Employee Referral Program
Corporate Sponsored Events & Community Outreach
Emergency Back-Up Childcare Program
Mobility Stipend