6+ years of experience in data engineering or related fields.
Hands-on experience with Databricks, Apache Spark, and Python.
Proven ability to build scalable data pipelines and frameworks.
Experience with data migration, validation, and quality controls.
Familiarity with Git-based development and CI/CD processes.
Experience leading teams in a client-facing environment.
Responsibilities
Lead Databricks data engineering and DataOps delivery.
Translate architecture and data models into technical designs.
Design and develop reusable data pipelines and transformation frameworks.
Establish coding and operational standards for data processes.
Troubleshoot Databricks job failures and performance issues.
Support batch and streaming data-processing patterns.
Coordinate technical delivery with various stakeholders.
Mentor data engineers and promote best practices.
Communicate technical decisions and impacts to leadership.
Benefits
Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Parental Leave and Adoption Assistance
401(k) Retirement Plan
Tuition Reimbursement and Skills Development Opportunities
Emergency Back-Up Childcare Program
Mobility Stipend
Full Job Description
Job Family: Data Science Consulting
Travel Required: Up to 25%
Clearance Required: Ability to Obtain Public Trust
What You Will Do
Lead Databricks data engineering and DataOps delivery across ingestion, transformation, orchestration, migration, integration, serving, and consumption patterns.
Translate architecture, data models, mappings, data contracts, and migration requirements into scalable technical designs and delivery plans.
Design and develop reusable pipelines, migration utilities, transformation frameworks, data-quality controls, reconciliation routines, and governed data products.
Establish standards for coding, testing, CI/CD, deployment, observability, logging, error handling, performance, security, and operational support.
Lead engineering reviews and troubleshoot Databricks job failures, pipeline bottlenecks, data-quality issues, and performance problems.
Support batch and, where applicable, streaming data-processing patterns using Databricks, Apache Spark, and Delta Lake.
Coordinate technical delivery with data architects, source-system teams, integration engineers, security specialists, governance leads, testing teams, and business stakeholders.
Lead technical estimates, capacity planning, backlog refinement, sprint execution, release readiness, and stabilization activities.
Mentor data engineers and ensure reusable code, design patterns, runbooks, and lessons learned are adopted across later modernization waves.
Communicate technical decisions, risks, dependencies, and delivery impacts to client and program leadership.
What You Will Need
Bachelor's degree from an accredited universtiy.
Minimum SIX (6)+ years of experience.
Experience in data engineering, ETL/ELT, cloud data platforms, software development, or analytics engineering.
Hands-on experience designing and developing production Databricks solutions using Apache Spark, PySpark, Python, SQL, Delta Lake, notebooks, workflows, and jobs.
Experience building scalable batch data pipelines and reusable ingestion, transformation, and orchestration frameworks.
Experience with enterprise data migration, source-to-target mapping, data conversion, reconciliation, validation, and defect remediation.
Experience with Git-based development, automated testing, CI/CD, release management, and production stabilization.
Experience leading data engineers and delivering complex data solutions in a client-facing environment.
Ability to obtain and maintain a Federal Public Trust.
What Would Be Nice to Have
Databricks Certified Data Engineer Professional or comparable Databricks certification.
Experience with Unity Catalog, Delta Live Tables, Databricks Workflows, Auto Loader, or related platform capabilities.
Experience with cloud storage, identity and access management, secrets management, networking, and platform security.
Experience with Azure DevOps, GitHub Actions, Jenkins, Terraform, or other infrastructure-as-code and deployment tools.
Experience developing APIs, data services, integration patterns, or event-driven pipelines.
Experience modernizing HR, ERP, workforce, financial, or other sensitive enterprise data.
Experience supporting federal agencies, regulated organizations, or public-sector modernization programs.
Experience with Agile Scrum or Kanban delivery.
The annual salary range for this position is $130,000.00-$216,000.00. 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
Position may be eligible for a discretionary variable incentive bonus
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
About Guidehouse
Guidehouse is a management consulting firm headquartered in Washington, D.C. The firm provides consulting services to clients in the public and commercial sectors, with a focus on energy, financial services, healthcare, national security, and aerospace and defense. Guidehouse was founded in 2018 as a spin-off from PwC. The firm has over 7,000 employees and operates in more than 50 locations worldwide.
