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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AWS Databricks Engineer - **Company:** Credence Management Solutions, LLC - **Location:** McLean, VA, United States - **Salary:** $155,000.0 - $185,000.0 - **Contract:** Permanent contract - **Skills:** OpenTofu, Artificial Intelligence, Amazon Web Services, Amazon S3, Big Data, Cloud Computing Security, Cloud Database, Cloud Engineering, Code Review, Cyber Security, Information Systems, Continuous Integration, Data as a Services, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Security, Data Systems, Software Design Documents, DevOps, Github, Identity and Access Management, Python (Programming Language), Operational Databases, Cloud Services, SQL Databases, Unstructured Data, AWS Cdk, Data Processing, Delivery Pipeline, Apache Spark, Infrastructure as Code (IaC), Gitlab, Git, Cloudformation, SC Clearance, Data Layers, Pandas, Data Lakes, Pyspark, Infrastructure Automation Frameworks, Information Technology, Deployment Automation, AWS Data Analytics, Data Management, Data Lakehouse, Functional Programming, Cloudwatch, Terraform, Data Pipelines, Jenkins, Databricks - **Published:** November 5, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9292669/aws-databricks-engineer ## About the Role * U.S. citizenship with the ability to obtain and maintain a Secret clearance is required. * Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related technical field. * Hands-on experience in data engineering, cloud engineering, or related technical roles. * Hands-on experience building and maintaining production data solutions using Databricks, Apache Spark, and PySpark. * Strong experience with AWS data services such as S3, Glue, RDS, Redshift, Lambda, IAM, and CloudWatch. * Strong understanding of ETL/ELT processes, data lake and lakehouse architectures, data modeling, and large-scale data processing. * Hands-on experience with Delta Lake, SQL, Python, and Spark-based data processing. * Experience developing, scheduling, monitoring, and troubleshooting production data pipelines and workflows. * Experience with Git and CI/CD platforms such as GitLab, GitHub Actions, Jenkins, or AWS CodePipeline. * Understanding of cloud security, identity and access management, encryption, and secure data-handling practices. * Strong communication skills and a client-oriented mindset with the ability to collaborate across technical and non-technical teams. Preferred * Experience implementing Databricks Lakehouse Architecture and medallion architecture using Bronze, Silver, and Gold data layers. * Experience with Databricks Unity Catalog, Delta Live Tables, Databricks Workflows, or similar data orchestration and governance capabilities. * Strong Python proficiency and experience with data engineering libraries and frameworks such as PySpark, Pandas, and Pydantic. * Experience with Infrastructure as Code tools such as Terraform, OpenTofu, AWS CDK, or CloudFormation. * AWS and/or Databricks certifications, such as AWS Certified Data Engineer - Associate, AWS Certified Solutions Architect, or Databricks Certified Data Engineer credentials. * Knowledge of federal cybersecurity, RMF, FedRAMP, or other government regulatory and compliance frameworks. * Experience delivering cloud-native data solutions within federal government or other highly regulated environments. ## Description Credence has an immediate need for an AWS Databricks Engineer to join our growing AI and Automation practice. You will serve as a key technical contributor responsible for designing, building, and optimizing scalable cloud-based data solutions using AWS and Databricks. You'll develop robust data pipelines, implement modern data lakehouse architectures, and collaborate across engineering, data science, and stakeholder teams to deliver secure, high-performance data capabilities that advance federal missions. Responsibilities include, but are not limited to, the duties listed below: * Databricks Engineering Design, build, and optimize scalable data pipelines and processing workflows using Databricks, Apache Spark, PySpark, and Delta Lake. * Data Lakehouse Architecture Design and implement modern lakehouse solutions using Databricks and AWS services. Apply medallion architecture (Bronze/Silver/Gold layers) to improve data quality, governance, lineage, performance, and accessibility. * AWS Data Integration 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. * Data Transformation & Optimization Develop efficient data transformation workflows using SQL, Python, and PySpark. Optimize Spark workloads, queries, clusters, and storage configurations for performance, reliability, and cost efficiency. * Data Governance & Quality Implement data quality, cataloging, lineage, governance, and access-control practices across Databricks and AWS environments, including the use of Unity Catalog where applicable. * Cloud Automation & DevOps Automate data platform deployments and workflows using Infrastructure as Code (IaC), CI/CD pipelines, Git-based development practices, and AWS-native deployment tools. * Collaborative Engineering Work closely with data engineers, software engineers, data scientists, cloud engineers, and mission stakeholders to translate business and technical requirements into production-ready data solutions. * Technical Rigor & Documentation Develop clean, maintainable, and well-documented code while following engineering, security, and federal development standards. Support code reviews, testing, troubleshooting, and technical design documentation.