Data Engineer

LMI has an immediate need for a Data Engineer to work with our NASA client in Washington, DC. The ideal candidate will have strong data engineering expertise and can review human capital related information. We are looking for someone able to extract datasets from different sources, coordinate the cleaning process, maintain data integrity, and prepare them for client use in their enterprise data environment. This person will also serve as a lead consultant to identify and collect customers' analytic and architectural requirements.

LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.

Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors-helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

Serve as an advisor to our NASA OCHCO (Office of the Chief Human Capital Officer) customer while leading development in data engineering activities
• Develop, implement and maintain a data pipeline using the Databricks platform, including extracting datasets using APIs, manipulating common data formats (e.g., parquet, text files, JSON), and automating routine data refreshes
• Build AWS resources to support data pipelining, storage, and analysis efforts
• Research and recommend software, systems, and processes as needed
• Be an effective consultant, including gathering analytic requirements to provide clear and concise solutions.
• Work in a fast-paced, solutions-oriented environment focused on client deliverables, analysis, and reporting.
• Conduct extensive quality control and record keeping procedures to ensure the highest levels of data integrity

Minimum Qualifications:

• Bachelor's Degree (Master's preferred) in a STEM or social science related field including coursework in basic statistics and measurement is required
• 3+ years of related data engineering or technical consulting experience
• Experience developing and automating data pipelines using Databricks
• Proficient in Python for object-oriented programming, automation, and data analysis; also experienced with computational tools such as R.
• Experience with ETL processes, including ingesting data from raw sources (APIs, web scraping), transforming them into usable formats for analysis, and validating them with automated checks
• Hands-on experience with GitHub for version control.
• Familiarity with GitHub Projects for task management.
• Experience building out common AWS infrastructure (e.g. EC2, S3, Lambda rules)
• Working knowledge of databases and SQL; preferred qualifications include linking analytic and data visualization products to database connections
• Excellent communication skills and proven ability to work with business customers and technical teams

Preferred experience in the following areas:

• Experience with Human Capital Data Analytics and ability to synthesize HR/Staffing data to create meaningful information that supports decision-making
• Experience with automation of recurring reports
• Performing data analysis and/or creating and applying HR performance metrics is desired
• Data science methods related to data architecture, data munging, data and feature engineering, and predictive analytics
• Experience creating and maintaining GitHub Actions workflows for automation or CI/CD.
• Bonus skill sets valued by the customer:
  • Developing machine learning, data mining, statistical network, natural language processing, text analytics, and graph-based algorithms to analyze massive data sets
  • Supervising algorithm implementation in on-premise and cloud-based computing environments
  • Experience creating meaningful data visualizations and interactive dashboards using platforms such as Tableau, Power BI, RShiny, and plotly to communicate findings