Research Data Manager

Axle • Bethesda, MD

11d

About The Position

Axle is a bioscience and information technology company focused on translational research, biomedical informatics, and data science. The Research Data Manager will build and maintain data infrastructure for the SOM Center, including its Laboratory Information Management System (LIMS), document and repository platforms such as Invenio, and connected metadata databases and pipelines. The role integrates instrument, assay, and analysis data to make it findable, traceable, and reusable in alignment with NIH data management and sharing requirements. It combines hands-on software development with data stewardship and uses cloud-native tooling and AI/ML to improve data discovery and use.

The position also evaluates data-management tools and standards, prepares technical assessments for IDSS leadership, trains laboratory and analytical staff, and develops standard operating procedures and technical documentation. Axle states its commitment to equal employment opportunity and provides an accommodation contact at [email protected].

Requirements

• Ability to integrate laboratory instruments, analysis pipelines, and external data sources with a LIMS and build automated ingestion pipelines with validation, logging, and error handling.
• Ability to write and maintain scripts and services to convert, normalize, and harmonize heterogeneous data formats into standardized schemas.
• Ability to deploy, configure, and support document and research data-management systems and manage records, metadata schemas, persistent identifiers, and access controls.
• Ability to design, create, and maintain databases for experimental metadata and small-to-moderate datasets, including schema design, migrations, indexing, backup, and recovery.
• Ability to incorporate AI/ML into data workflows and user interfaces, including semantic search, metadata extraction and auto-annotation, and natural-language query tools.
• Ability to develop, containerize, and deploy software on cloud or local Kubernetes resources and maintain CI/CD pipelines, monitoring, and infrastructure-as-code.
• Ability to evaluate and recommend data-management packages, platforms, and standards and prepare technical assessments.
• Ability to train laboratory and analytical staff and write standard operating procedures and technical documentation.

Nice To Haves

• Experience deploying or customizing Invenio/InvenioRDM or similar repositories such as Dataverse, DSpace, or CKAN.
• Experience integrating ML/AI components into applications, such as embeddings and vector search, LLM-based retrieval, or document parsing.
• Familiarity with workflow tools such as Airflow, Nextflow, Snakemake, or Argo, and with Helm, Terraform, or similar infrastructure-as-code tools.
• Experience with stem cell or tissue engineering laboratories.
• Experience with imaging and omics data.
• Experience with high-performance computing environments, such as NIH Biowulf.
• Experience with front-end tooling such as React for data-facing interfaces.

Responsibilities

• Connect laboratory instruments, analysis pipelines, and external data sources to the LIMS.
• Build and maintain automated data-ingestion pipelines with validation, logging, and error handling.
• Write and maintain scripts and services to convert, normalize, and harmonize heterogeneous data formats into standardized schemas.
• Deploy, configure, and support document and research data-management systems such as Invenio; manage records, metadata schemas, persistent identifiers, and access controls.
• Design, create, and maintain databases for experimental metadata and small-to-moderate datasets, including schema design, migrations, indexing, backup, and recovery.
• Incorporate AI/ML into data workflows and user interfaces, including semantic search, metadata extraction and auto-annotation, and natural-language query tools.
• Develop, containerize, and deploy software on cloud or local Kubernetes resources.
• Maintain CI/CD pipelines, monitoring, and infrastructure-as-code.
• Evaluate and recommend data-management packages, platforms, and standards, and prepare short technical assessments for IDSS leadership.
• Train laboratory and analytical staff and write standard operating procedures and technical documentation.

Benefits

• 100% medical, dental, and vision coverage for employees
• Paid time off and paid holidays
• 401(k) match up to 5%
• Educational benefits for career growth
• Employee referral bonus
• Flexible Spending Accounts, including Healthcare FSA, Parking Reimbursement Account (PRK), Dependent Care Assistance Program (DCAP), and Transportation Reimbursement Account (TRN)

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed