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Credence

Federal government management, engineering, technology solutions

AWS Databricks Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeMcLean, VA, USA$155k - $185k /yrIn-person

About the Job

Requirements

  • U.S. citizenship and the ability to obtain and maintain a Secret clearance are required.
  • A bachelor's or master's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related technical field is required.
  • Hands-on experience in data engineering, cloud engineering, or related technical roles is required.
  • Hands-on experience building and maintaining production data solutions using Databricks, Apache Spark, and PySpark is required.
  • Strong experience with AWS data services such as S3, Glue, RDS, Redshift, Lambda, IAM, and CloudWatch is required.
  • A strong understanding of ETL/ELT processes, data lake and lakehouse architectures, data modeling, and large-scale data processing is required.
  • Hands-on experience with Delta Lake, SQL, Python, and Spark-based data processing is required.
  • Experience developing, scheduling, monitoring, and troubleshooting production data pipelines and workflows is required.
  • Experience with Git and CI/CD platforms such as GitLab, GitHub Actions, Jenkins, or AWS CodePipeline is required.
  • An understanding of cloud security, identity and access management, encryption, and secure data-handling practices is required.
  • Strong communication skills and a client-oriented mindset, including the ability to collaborate across technical and non-technical teams, are required.

Responsibilities

  • Design, build, and optimize scalable data pipelines and processing workflows using Databricks, Apache Spark, PySpark, and Delta Lake.
  • Design and implement modern lakehouse solutions using Databricks and AWS services, applying medallion architecture with Bronze, Silver, and Gold layers to improve data quality, governance, lineage, performance, and accessibility.
  • Build and maintain ETL/ELT pipelines integrating structured, semi-structured, and unstructured data across AWS services such as S3, Glue, RDS, Redshift, Lambda, and related cloud data platforms.
  • Develop efficient data transformation workflows using SQL, Python, and PySpark; optimize Spark workloads, queries, clusters, and storage configurations for performance, reliability, and cost efficiency.
  • Implement data quality, cataloging, lineage, governance, and access-control practices across Databricks and AWS environments, including Unity Catalog where applicable.
  • Automate data platform deployments and workflows using Infrastructure as Code, CI/CD pipelines, Git-based development practices, and AWS-native deployment tools.
  • Work with data engineers, software engineers, data scientists, cloud engineers, and mission stakeholders to translate business and technical requirements into production-ready data solutions.
  • Develop clean, maintainable, well-documented code following engineering, security, and federal development standards, and support code reviews, testing, troubleshooting, and technical design documentation.

Desired Qualifications

  • An active Secret clearance is preferred.
  • CompTIA Security+ (Sec+) certification is preferred.
  • Databricks certifications are preferred.
  • Experience implementing Databricks Lakehouse Architecture and medallion architecture using Bronze, Silver, and Gold data layers is preferred.
  • Experience with Databricks Unity Catalog, Delta Live Tables, Databricks Workflows, or similar data orchestration and governance capabilities is preferred.
  • Strong Python proficiency and experience with data engineering libraries and frameworks such as PySpark, Pandas, and Pydantic are preferred.
  • Experience with Infrastructure as Code tools such as Terraform, OpenTofu, AWS CDK, or CloudFormation is preferred.
  • AWS and/or Databricks certifications, such as AWS Certified Data Engineer - Associate, AWS Certified Solutions Architect, or Databricks Certified Data Engineer credentials, are preferred.
  • Knowledge of federal cybersecurity, RMF, FedRAMP, or other government regulatory and compliance frameworks is preferred.
  • Experience delivering cloud-native data solutions within federal government or other highly regulated environments is preferred.

About the Company

Credence

Federal government management, engineering, technology solutions

Credence provides management, engineering, and technology solutions to the Federal Government, focusing on helping government programs that are complex and technical. Its work is delivered through an independent and objective approach, acting as a trusted partner to customers and teaming partners to achieve mission goals. The company differentiates itself through a track record of recognition in the government contracting space, a culture that emphasizes employee empowerment and a values framework of Trust, Partnership, and Success, and a commitment to delivering measurable outcomes for clients. Credence aims to support government missions by providing high-quality services that ensure project success, while also giving back to the community through charitable involvement and volunteerism.

Company size
501-1,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Vienna, VA
Founded
2005

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