HOW A DATA ENGINEER WILL MAKE AN IMPACT
Design, implement, and maintain scalable extract-transform-load and extract-load-transform (ETL/ELT) pipelines on the Government-furnished technology stack (e.g., SQL Server, Databricks, and Apache Spark (PySpark)) for batch and scheduled processing and data transformation.
Fuse disparate structured, semi-structured, and unstructured data sources from across the POTFF enterprise, including the Government-designated Human Performance System of Record (e.g., HPDMS), assessment and wearable data, and other Government-approved systems, into curated, analysis-ready datasets.
Implement rigorous data quality controls, validation rules, lineage documentation, and performance tuning to ensure reliable, reproducible, and secure pipelines; monitor scheduled and orchestrated workloads and resolve failures.
Develop and maintain data models, data dictionaries, metadata, and transformation logic under version control, and document data sources, assumptions, and processing steps to ensure transparency and operational continuity.
Prepare and curate text and other unstructured data to support Natural Language Processing (NLP) and Large Language Model (LLM) use cases executed by the data science team within Government-approved tools.
Support the integration of curated data products into Government-furnished visualization and low-code tools and the deployment of analytic products into operational workflows, including basic machine-learning operations (MLOps) practices where directed by the Government.
Apply Government data governance, security, and privacy requirements, including DoW Impact Level 5 (IL5), HIPAA, and Privacy Act protocols, to all data handling, and implement data access controls as directed by the Government.
Collaborate with Government personnel, clinicians, program staff, and the data science team to identify new data sources, improve the quality of data entered into Government systems, and translate analytical requirements into data requirements.
Provide data engineering expertise and technical guidance to Data Scientists and Senior Data Scientists.
WHAT YOU’LL NEED TO SUCCEED
EDUCATION
Bachelor’s degree in a quantitative or computing discipline, including but not limited to computer science, computer engineering, software engineering, information systems, data science, data engineering, mathematics, statistics, or geospatial science or geoinformatics, with documented coursework or professional application in programming, databases, and quantitative analysis. A candidate without the degree qualifies with the experience stated under Required Minimum Experience/Skills.