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Senior Software Engineer — Python | Data Governance and Analytics

Thermofisher

Skills

Required

  • Python
  • async programming
  • data structures
  • performance optimization
  • modular architecture
  • Python packaging
  • dependency management
  • error handling
  • automated testing
  • data analytics
  • SQL
  • relational/non-relational data modelling
  • GitLab / GitHub
  • Docker
  • K8s

Preferred

  • software engineering
  • backend development / data engineering / analytics platforms
  • data ingestion pipelines
  • data models
  • analytics backends
  • data governance standards
  • metadata tracking
  • data lineage mechanisms
  • data extraction

Standard (Mon-Fri) Environmental Conditions Office Job Description Experience Level: 6–9 Years Team: Data Governance and Analytics Organization: Data, AI, and Visualization (DAIV), Global Software R&D About the team

About the role We are seeking a Senior Software Engineer with deep technical expertise in Python and Data Governance & Analytics (DGA) systems. In this role, you will design, build, and scale high-performance data pipelines, analytics infrastructure, and governance frameworks that empower our engineering and product teams. You will work closely with cross-functional architecture and DevOps teams to drive automated data ingestion, ensure stringent data quality, and build reliable backend services that support critical operational metrics and reporting.

About Thermofisher

  • The Data Governance and Analytics Team is part of Data, AI, and Visualization (DAIV) within our global software R&D organization.
  • We are a diverse, distributed team with colleagues across France and the Netherlands.
  • We bring digital technology into our products, solutions, and services, enabling data extraction, analysis, and connectivity.
  • We develop software that supports data governance by managing data definitions, improving data quality, and making data more usable and useful.
  • Our work prepares the organization for the age of AI, supports data-driven design, and enables value creation from data.

Responsibilities

  • Design, develop, test, and scaling of robust data ingestion pipelines, data models, and analytics backends using Python .
  • Implement and automate data governance standards, metadata tracking, and data lineage mechanisms to ensure high data integrity, security, and compliance.
  • Build capabilities supporting data extraction, processing, analysis, connectivity, and governance.
  • Implement data validation and transformation logic to improve consistency, quality, and usability.
  • Develop clear interfaces that enable other teams to integrate and reuse Python components.
  • Identify opportunities to reuse existing software and simplify implementation across projects.
  • Structure Python code into maintainable modules and packages with appropriate dependency management.
  • Collaborate with architects to define component interfaces, dependencies, and integration approaches.
  • Write automated tests and maintain reliable test coverage for critical functionality.
  • Participate in code reviews and improve code readability, reliability, and maintainability.
  • Investigate defects, troubleshoot software and integration issues, and improve performance where. needed.
  • Maintain technical documentation and clear runbooks covering component interfaces, configuration, integration dependencies, and usage.
  • Collaborate with software architects and engineers across the wider R&D organization.
  • Establish strong reliability practices (logging/monitoring, retries/backoff, idempotency, concurrency controls, safe cleanup, traceability).
  • Mentor engineers through code reviews, best practices, and technical leadership.
  • Work effectively within an Agile Scrum / SAFe framework , participating in backlog refinement, sprint planning, technical estimation, PI planning, reviews, retrospectives, and cross-team coordination to support predictable and high-quality delivery.

Requirements

  • Skills Expert-level proficiency in Python (async programming, data structures, performance optimization, and modular architecture).
  • Experience developing shared Python packages or libraries used by other engineering teams.
  • Ability to independently develop, test, debug, and maintain Python modules and libraries.
  • Understanding of Python packaging, dependency management, error handling, and automated testing.
  • Experience manipulating data, including cleaning, transforming, validating, or aggregating datasets.
  • Knowledge of data analytics concepts. · Strong foundation in SQL, relational/non-relational data modelling, and data transformation frameworks. · Experience with data governance principles (data quality frameworks, cataloguing, lineage, and metadata management).
  • Ability to collaborate effectively with colleagues across locations and disciplines.
  • Ability to design modular, reusable, and maintainable software.
  • Experience working in an agile DevOps environment.
  • Experience using GitLab or GitHub for source control and collaborative development.
  • Familiarity with build pipelines, test automation, and automated deployment.
  • Understanding of containerization concepts, with familiarity with technologies such as Docker, K8s, Helm, etc Working knowledge of Agile delivery frameworks, including Scrum and SAFe, with experience operating effectively in sprint-based and cross-team planning environments.
  • Strong communication and stakeholder management skills, with the ability to work effectively across global, cross-functional teams.
  • Experience operating in structured product-development environments with strong quality, compliance, and delivery expectations.

Preferred

  • Qualifications Bachelor’s or master’s degree, preferably in a technical or scientific discipline.
  • 6+ years of software engineering experience with a strong focus on backend development, data engineering, or analytics platforms.