Data Architect (Waltham, MA)

Highbrow LLC; Waltham (MA); On-site; USD 100,000 - 130,000; Full time

Job summary

A healthcare technology firm in Waltham, MA seeks a skilled Data Engineer to design systems for clinical and imaging data. The ideal candidate has a background in Computer Science and 6+ years of relevant experience, particularly in Python and AWS. Responsibilities include developing data architectures, ensuring compliance with regulations like HIPAA, and collaborating with diverse engineering teams. This role operates onsite three days a week starting from day one, offering a dynamic work environment focused on innovation and patient safety.

Qualifications

• 6+ years of relevant work experience with a Bachelor’s degree.
• 3+ years of relevant work experience with a Master's or PhD.
• Strong understanding of relational databases and clinical data models.

Responsibilities

• Design a systems level architecture for clinical, device, and imaging data.
• Ensure high-throughput image ingestion, indexing, and retrieval.
• Collaborate closely with data scientists and engineers.

Skills

Python

AWS

CI/CD pipelines

Relational databases

Machine learning operations

SQL

Medical imaging data

Communication skills

Education

Bachelor’s degree in Computer Science, Software Engineering or related field

Master’s or PhD

Tools

Terraform

CloudFormation

AWS CDK

Pandas library

Atlassian Tool Chain

Job description

Location – Waltham, MA (3 days a week, onsite from day 1)

NOTE: This position requires recent experience with Healthcare companies and Snowflake.

Job Description:

Required:

• Bachelor’s degree or higher in Computer Science, Software Engineering, Data Science, Biomedical Engineering or related field.
• 6+ Years of relevant work experience with Bachelor’s degree.
• 3+ Years of relevant work experience with Masters or PhD.
• 4+ years of consistent coding in Python.
• Strong understanding and use of relational databases and clinical data models.
• Experience working with medical imaging data (DICOM), computer vision algorithms and tools.
• Experience with AWS and cloud technologies and AWS DevOps tools.
• Experience with creating and managing CI/CD pipelines in AWS.
• Experience with Infrastructure as Code (IaC) using Terraform, CloudFormation or AWS CDK.
• Excellent organizational, communication, and collaboration skills.
• Foundational knowledge in machine learning (ML) operations and imaging ML pipelines.

Preferred Qualifications:

• Experience with software validation in a regulated industry
• Experience with Cloud imaging tools (ex. AWS Health Imaging, Azure Health Data Services)
• Working knowledge of data de-identification/pseudonymization methods
• Manipulating tabular metadata using SQL and Python’s Pandas library
• Experience with the Atlassian Tool Chain
• Data and annotation version control tools and processes
• Knowledge of HIPAA, FDA regulations (21 CFR Part 11), GDPR for medical device data governance.

Job Responsibilities:

• Design a systems level architecture for clinical, device, and imaging data and pipelines to support machine learning & classical algorithm development throughout the product lifecycle.
• Ensure architecture supports high-throughput image ingestion, indexing, and retrieval.
• Advance conceptual, logical, and physical data models for structured, semi-structured, and unstructured data.
• Help define and document data standards and definitions.
• Implement governance frameworks that enforce healthcare and data regulations to data architecture (HIPAA, FDA Part 11, GDPR, etc.).
• Performs strategic validation tasks of data management tools and platforms
• Collaborate closely with data scientists, cloud data engineers, algorithm engineers, clinical engineers, software engineers and systems engineers locally and globally.
• Investigate, research, and recommend appropriate software designs, machine learning operations, tools for dataset organization, controls, and traceability.
• In all actions, lead with integrity and demonstrate a primary commitment to patient safety and product quality by maintaining compliance to all documented quality processes and procedures.