Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

As part of the Thermo Fisher Scientific team, you'll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the world's toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer.

DESCRIPTION:

As a Data Analyst II at Thermo Fisher Scientific, you'll contribute to transforming complex data into actionable insights that drive strategic business decisions. You'll work closely with cross-functional teams to collect requirements, analyze data, and develop scalable solutions using advanced analytics tools. This role combines technical expertise with business acumen to deliver results that support our mission of enabling customers to make the world healthier, cleaner and safer.

You'll develop and maintain interactive dashboards and reports using tools like Power BI to provide crucial business intelligence across the organization. Through SQL queries and data analysis, you'll identify trends, discover opportunities for improvement, and make data-driven recommendations. Your work will directly impact key performance indicators and strategic initiatives while maintaining the highest standards of data quality and integrity.

In this collaborative environment, you'll have opportunities to enhance processes, automate workflows, and implement innovative solutions. You'll serve as a technical resource for stakeholders, providing training and support while maintaining strong partnerships across the organization.

Position Summary

The Data Engineer / Analytics Engineer II is responsible for designing, building, and maintaining scalable data infrastructure and data products that enable commercial analytics and data-driven decision-making.

This role bridges business and technology, transforming complex, multi-source commercial data into reliable, high-performance data models, pipelines, and data marts that support reporting, analytics, and data science initiatives. This position will have to be flexible to work the US hours.

Key Responsibilities

Data Engineering & Pipeline Development

Design, build, and maintain scalable data pipelines for structured and unstructured commercial data
Develop and optimize ETL/ELT processes using Python, SQL, and orchestration tools (e.g., Airflow)
Automate data workflows and integrations across sales, finance, pricing, and operational systems
Drive integration of ChatGPT and LLM activities through scalable prompt-driven development workflows, and operationalizing AI-assisted engineering projects

Data Architecture & Modeling

Design and implement data marts and scalable data architectures
Apply dimensional modeling techniques (star, snowflake schemas)
Ensure data models are optimized for performance, usability, and scalability

Data Integration & Systems

Integrate data from CRM systems, financial systems, and other enterprise platforms
Develop APIs and data services to enable downstream consumption
Ensure data consistency, governance, and quality across platforms

Analytics Enablement

Partner with analysts and data scientists to deliver clean, reliable datasets
Support Power BI/Tableau reporting infrastructure (datasets, dataflows, DAX)
Enable self-service analytics through well-structured data layers

Advanced Analytics & Data Science Support

Support or lead advanced analytics initiatives, including predictive modeling
Perform advanced data analysis using Python and related libraries
Translate business requirements into scalable technical solutions

Project & Stakeholder Management

Lead complex data projects from design through delivery
Collaborate with IT, sales, finance, and analytics teams
Balance ad hoc requests with long-term platform development

Day-to-Day Activities

Build and maintain data pipelines and workflows
Write and optimize complex SQL queries
Design and evolve data models and data marts
Troubleshoot data issues across systems and dashboards
Collaborate with stakeholders to translate requirements into scalable data solutions

Required Qualifications

4–5+ years of experience in data engineering or analytics engineering
Strong proficiency in:

SQL (advanced queries, performance tuning)
Python (data processing, automation)

Experience with:

Data warehousing (e.g., Redshift, AWS)

At Thermo Fisher Scientific, each one of our 75,000 extraordinary minds has a unique story to tell. Join us and contribute to our singular mission—enabling our customers to make the world healthier, cleaner and safer.

Thermo Fisher Scientific is an EEO/Affirmative Action Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other legally protected status.