Data Engineer at ThermoFisher Scientific

Setup: Hybrid
Type: Full-time

Description

ThermoFisher Scientific Inc. is seeking a Data Engineer to strengthen their data engineering capabilities. The role involves designing, building, testing, and optimizing data pipelines for enterprise data platform (EDP) solutions, collaborating with cross-functional teams, ensuring data quality, and supporting architectural evolution. The ideal candidate will have extensive experience in data solution delivery, particularly with Cloud BI solutions using AWS or Azure, and strong proficiency in SQL, PySpark, and Python.

Required Skills

Source to Target Data Mapping
Data Pipeline Optimization
Real-Time/Batch Processing
Requirement Analysis
Product Backlog Management
Risk Mitigation Planning
Agile Methodologies
DevOps Practices
Large Language Models

Additional Information

Required Previous Experiences: 6+ years of overall work experience with 4+ years exclusively in delivering data solutions.
3+ years of proven experience building Cloud BI solutions using AWS or Azure.
Experience with agile development methodologies by following DevOps, Data Ops and Dev Sec Ops practices.
4+ years of programming in SQL, Pyspark and Python.
Preferred Qualifications: Hands on experience with Snowflake or Azure data engineering.
Knowledge of SQL and NoSQL databases like PostgreSQL, MySQL, MongoDB Cassandra.
Experience in building data pipelines in Databricks.
Data visualization experience using tools such as Power BI or Tableau.
Knowledge of data governance practices, data quality, and data security.
Relevant certifications in data engineering on cloud platforms.
Basic understanding of machine learning and Generative AI concepts.