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Data Engineer​/Python Developer

Job in Boston, Suffolk County, Massachusetts, 02298, USA
Listing for: Zifo
Full Time position
Listed on 2026-03-06
Job specializations:
  • Software Development
    Data Engineer, Python
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Zifo is a global specialist scientific and process informatics services company supporting life sciences, biotech, and pharmaceutical organizations. We enable digital transformation across R&D, manufacturing, and quality by delivering data-driven, scalable, and compliant software solutions.

Zifo is seeking a passionate Software Developer who can work at the intersection of science, data, and technology. The role requires strong expertise in Python, SQL/No

SQL, AWS, FastAPI, and Benchling, along with the ability to work directly with scientists performing assay-based experiments. The successful candidate will translate experimental workflows into robust data components, scientific system integrations, AI-enabled insights, and next-generation data pipelines.

Location: Boston, MA, RTP North Carolina.

Requirements
  • Collaborate with scientists, assay teams, and lab operations to capture end-to-end assay and experimental workflows, from sample onboarding and execution through data ingestion, validation, and downstream analytics
  • Translate scientific and operational requirements into well-defined functional, technical, and data requirements for laboratory platforms, system integrations, and next-generation data pipelines
  • Design, develop, and maintain Python-based backend services, APIs, and data pipelines on AWS
  • Build backend services using FastAPI and supporting frameworks such as Flask or Django
  • Develop and maintain RESTful APIs and microservices for integration with scientific systems including Benchling, LIMS, ELN, CDS, and SDMS
  • Design and optimize SQL and No

    SQL data models to support structured, semi-structured, and high-volume scientific data
  • Build and support ETL/ELT and next-generation data pipelines for analytics and AI/ML workloads
  • Support AI/ML use cases by preparing datasets, enabling feature engineering, and integrating models into pipelines and applications
  • Implement and maintain CI/CD pipelines for automated build, testing and deployment
  • Apply Test-Driven Development (TDD) practices and develop automated unit, integration, and data validation tests
  • Ensure solutions meet performance, data integrity, security, and regulatory compliance requirements (e.g., GxP, 21 CFR Part 11)
  • Perform code reviews, debugging, and performance optimization
  • Coordinate across cross-functional and geographically distributed teams, managing dependencies and ensuring delivery alignment
  • Create ready to deliver technical documentation and track deliverables using JIRA and Confluence
Required Qualifications
  • Bachelor's or master's degree in computer science, Engineering, Life Sciences with 2-5 years of hands‑on experience in Python development with FastAPI (Flask or Django is a plus)
  • Proficiency in SQL, including schema design, complex queries, and performance optimization; relational databases such as Postgre

    SQL, MySQL, Oracle, AWS RDS/Aurora;
    No

    SQL databases such as Dynamo

    DB, Mongo

    DB, or equivalent
  • Solid understanding of REST APIs, microservices, and integration patterns
  • AWS experience, including S3, EC2, Lambda, Step Functions, RDS/Aurora, IAM, monitoring, and logging
  • Proficiency with Git‑based collaborative development, including branch management, pull requests, code reviews, and integration with CI/CD pipelines (Git Hub Actions, Git Lab CI, Jenkins, AWS Code Pipeline) to ensure reliable and traceable software delivery
  • Hands‑on experience with Test‑Driven Development and Python testing frameworks such as pytest, unittest, and mocking libraries
  • Working knowledge of AI/ML concepts, including data preparation, feature engineering, model integration, and inference workflows
  • Exposure to the data and ML libraries such as pandas, Num Py, and scikit‑learn (exposure to Tensor Flow or PyTorch is a plus)
  • Exposure to life sciences, biotech, pharma, or healthcare domains and scientific platforms such as LIMS, ELN, SDMS, CDS, or data lakes
  • Ability to design data models aligned to scientific and assay workflows & integrating scientific or enterprise systems and working directly with scientists or lab users
  • Knowledge of containerization (Docker) and modern deployment best practices
  • Familiarity with Agile/Scrum & SDLC development methodologies
  • Strong…
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