Data Engineer

About

Ever‑expanding technology like IoT, machine learning, and artificial intelligence means that there's more structured and unstructured data available today than ever before. As a data engineer, you know that organizing data can yield pivotal insights when it's gathered from disparate sources. We need an experienced data engineer like you to help our clients find answers in their data to impact important missions.

As a Data Engineer on our team, you'll implement data engineering activities and strategy on some of the most mission‑driven projects in the industry. You'll design, deploy, and develop pipelines and platforms that organize and make disparate data meaningful. You’ll work with a multi‑disciplinary team of data analysts, engineers, scientists, electrical engineers, test engineers, software developers, and data consumers in a fast‑paced, agile environment. You’ll assess, design, build, and maintain scalable data platforms, develop and maintain database systems, continually seek opportunities to optimize the organization’s data ecosystem, and build custom ETL and ELT workflows as necessary to address critical analytical questions.

Responsibilities

• Collaborate with cross‑functional teams to understand business requirements and translate them into technical solutions.
• Implement and manage data governance practices, ensuring data quality, security, and compliance.
• Design, construct, install, test, and maintain highly scalable data management systems, ensuring they meet business requirements and industry practices.
• Employ a variety of languages and tools to integrate systems or identify opportunities to acquire new data from other sources.
• Interpret and analyze data from various source systems to support data integration and reporting needs.
• Identify, design, and implement internal process improvements, including automating manual processes, optimizing data delivery, and re‑designing infrastructure for greater scalability.
• Develop and optimize database schemas and data models to support analytics and reporting.
• Create data tools for analytics and data‑science team members that assist them in building and optimizing our data products.
• Grow communication and technical skills by merging consulting and big data to create data‑centric solutions across the testing and evaluation industry.
• Stay updated with industry trends and emerging technologies to propose strategic improvements.

Requirements

• 2+ years of experience designing, building, and operating production ETL or ELT pipelines.
• 2+ years of experience with DBMS relational databases, including data modeling and schema design.
• 2+ years of experience using Python for data processing and automation.
• 1+ years of experience with cloud services.
• Experience integrating data from RESTful APIs and external data sources.
• Experience developing and deploying containerized workloads using Docker.
• Experience with workflow orchestration and CI/CD for data workloads.
• Experience implementing or contributing to logging, monitoring, alerting, and data validation for production pipelines.
• Ability to obtain a Secret clearance.
• Bachelor’s degree.

Preferred Qualifications

• 2+ years of experience with PostgreSQL.
• 1+ years of experience with AWS.
• Experience with container orchestration platforms, preferably Kubernetes.
• Experience with infrastructure‑as‑code (Terraform, CloudFormation, or CDK).
• Experience with PySpark or other distributed data processing frameworks.
• Experience with data quality frameworks or automated testing for data pipelines.
• Knowledge of security and access controls for cloud‑based data systems.
• Secret clearance.

Compensation & Benefits

• Projected annual compensation range: $61,900 – $141,000 (USD), dependent on location, education, experience, and other factors.
• Comprehensive benefits package including health, life, disability, financial, and retirement plans.
• Paid leave, professional development, tuition assistance, work‑life programs, and dependent care.
• Recognition awards program for exceptional performance.
• Eligibility for full benefit programs for full‑time and part‑time employees working at least 20 hours per week.