Data Engineer

Title: Data Engineer Location: Gaithersburg, MD

Data Engineer – Scientific Document and Data Pipelines

Responsible for designing, developing, and implementing automated scientific data extraction and standardization solutions supporting the National Institute of Standards and Technology (NIST) CHIPS METIS initiative. Develops advanced Python-based pipelines to extract figures, charts, and tables from scientific documents and transform non-standard research data into structured, machine-readable formats. Implements Optical Character Recognition (OCR), document layout analysis, data normalization, and schema validation capabilities. Integrates data processing tools and microservices into existing web applications and research data repositories. Works closely with government scientists and technical stakeholders to ensure data accuracy, accessibility, and interoperability. Develops technical documentation, maintains source code repositories, and supports the delivery of reliable, reusable software solutions.

Responsibilities / Tasks

• Design and implement automated OCR and document layout analysis pipelines to extract scientific figures, charts, and tables from PDF and Microsoft Word documents.
• Develop algorithms to identify and extract figure captions, axis labels, measurement units, and associated scientific metadata.
• Implement table extraction capabilities that preserve row and column structures, headers, and data relationships.
• Integrate extracted metadata with established controlled vocabularies and ontologies within the Controlled Vocabulary Curation System (CVCS).
• Develop and enhance user interfaces that enable scientific domain experts to validate extracted content and correct OCR errors.
• Develop Python-based parser libraries to convert proprietary instrument outputs, legacy spreadsheets, and non-standard text files into standardized CSV formats.
• Implement automated data normalization, schema validation, and quality assurance procedures to ensure compliance with METIS data schemas.
• Develop heuristic data-cleaning capabilities to address missing values, merged cells, inconsistent headers, and extraneous metadata.
• Integrate extraction and standardization tools as microservices or software modules within the existing CVCS web application architecture.
• Develop data export capabilities to support integration with the METIS Discovery Portal.
• Prepare design documentation, implementation guides, API specifications, and deployment procedures.
• Develop, test, and maintain documented source code within GitHub repositories, including code intended for public release.
• Prepare and deliver technical demonstrations of extraction workflows, data conversion capabilities, and system enhancements.
• Monitor and report technical performance metrics, including document processing volumes, OCR accuracy, data conversion success rates, and system integration status.
• Collaborate with government scientists, developers, and technical stakeholders to identify requirements, troubleshoot technical issues, and improve system functionality.

Required Skills:

• Bachelor's degree (four-year) in Computer Science, Data Engineering, or a related field.
• Four (4) years of advanced Python programming experience, specifically with Pandas and OCR libraries.
• Four (4) years of experience with OCR pipelines and table extraction logic.
• Four (4) years of experience with data format normalization and schema validation.
• Four (4) years of experience integrating microservices into web applications.
• Experience developing and maintaining automated data processing and transformation pipelines.
• Knowledge of OCR and document processing technologies such as Tesseract, PaddleOCR, pdfplumber, Camelot, LayoutParser, or comparable tools.
• Familiarity with JSON Schema, XML/XSD, controlled vocabularies, and ontology-based metadata tagging.
• Experience with REST APIs, GitHub, and software development and deployment practices.
• Strong analytical, problem-solving, technical documentation, and communication skills.
• Must be able to successfully complete a federal background investigation appropriate for an IT-Low Risk position and meet applicable HSPD-12/PIV credentialing requirements.
• Must be able to work on-site at the NIST campus in Gaithersburg, Maryland.
• This position is contingent upon contract award.