Data Engineer, Digitization Technology

Thermo Fisher Scientific • Grand Island, NY

2d • $66,000 - $90,000 • Onsite

About The Position

The Data Engineer, Digitization Technology is part of the Biologicals and Chemicals Division, one of the fastest-growing areas of the company, supporting developers and manufacturers of biological-based therapeutics and vaccines. This role contributes to the division’s digitization efforts by enabling reliable, high-quality experimental data to flow from laboratory systems into downstream analytical platforms. Working at the intersection of laboratory systems and the enterprise data platform, the Data Engineer plays a key role in ensuring experimental data is structured, interpretable, and ready for use in analytics, reporting, and future advanced data applications.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• Minimum of 2 years of relevant professional experience.
• At least 2 years of experience in a data engineering or data-focused software role, with exposure to technical, business, or operational data requirements.
• Experience working with data lakes, analytics platforms, or business intelligence solutions.
• Hands-on experience using Databricks or similar data processing platforms.
• Proficiency in Python and common Python libraries used for data processing and analysis.
• Experience working with SQL databases, including writing and optimizing queries, debugging data issues, and working with views, indexes, and user-defined functions.
• Ability to work effectively as part of a cross-functional team, collaborating with engineers, scientists, and data stakeholders.
• Comfortable working with complex, evolving datasets and addressing ambiguity in historical or experimental data.
• Demonstrated problem-solving skills and a willingness to learn and grow within a data engineering environment.

Nice To Haves

• Familiarity with laboratory or scientific data systems (e.g., LIMS) is preferred.

Responsibilities

• Develop, maintain, and support mission-critical data pipelines that move experimental data from laboratory systems (e.g., LIMS and ELN) into the division’s data lake.
• Ingest and curate historical experimental data, addressing inconsistencies, data quality issues, and evolving data structures to ensure downstream usability and trust.
• Maintain and support the LIMS environment, including troubleshooting data-related issues and collaborating with system stakeholders to resolve root causes.
• Apply data quality checks, validation logic, and monitoring to ensure accuracy, consistency, and completeness of ingested data.
• Collaborate closely with data architecture, data operations, and platform teams to align ingestion processes with established data standards and platform requirements.
• Support downstream analytics and reporting use cases by ensuring experimental data is well-structured, documented, and appropriately contextualized.
• Contribute to documentation of data pipelines, data structures, and ingestion processes to support transparency, reuse, and long-term maintainability.
• Continue to develop technical skills across data engineering, analytics, and visualization through hands-on work and collaboration with more senior engineers.

Benefits

• A choice of national medical and dental plans, and a national vision plan, including health incentive programs
• Employee assistance and family support programs, including commuter benefits and tuition reimbursement
• At least 120 hours paid time off (PTO), 10 paid holidays annually, paid parental leave (3 weeks for bonding and 8 weeks for caregiver leave), accident and life insurance, and short- and long-term disability in accordance with company policy
• Retirement and savings programs, such as our competitive 401(k) U.S. retirement savings plan
• Employees’ Stock Purchase Plan (ESPP) offers eligible colleagues the opportunity to purchase company stock at a discount

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level