Data Engineer​/Python Developer

Overview

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. We are 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, 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.

Boston, MA, RTP North Carolina.

• 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.

• 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).
• 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 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 and integrate scientific or enterprise systems, working directly with scientists or lab users.
• Knowledge of containerization (Docker) and modern deployment best practices.
• Familiarity with Agile/Scrum & SDLC development methodologies.
• Strong communication, stakeholder…