Location: Hyderabad
Job Type: Full Time
Salary: 100,000 – 120,000
Job Description
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.
About the Role
Join our pharmaceutical CDMO as a Data Engineer and help transform how data fuels innovation, compliance, and scientific progress. You’ll design and maintain modern data pipelines that power decisions across research, manufacturing, and quality operations.
What You’ll Do
Build and maintain scalable data pipelines to connect systems like LIMS, MES, and EHR.
Integrate and transform structured and unstructured data to enable advanced analytics.
Ensure accuracy and integrity through automated validation, cleansing, and monitoring.
Develop and optimize data architecture, including lakes, warehouses, and marts.
Collaborate with scientists, analysts, and IT to translate business needs into technical designs.
Implement governance frameworks that meet GxP, GCP, and HIPAA standards.
Use cloud platforms (AWS, Azure, or GCP) and orchestration tools (Airflow, dbt, or Spark) to streamline operations.
Document pipelines and maintain clear data lineage for transparency and audit readiness.
Stay current with emerging data technologies to drive continuous improvement.
What You Bring
Bachelor’s or Master’s degree in Computer Science, Engineering, or a quantitative field.
4+ years of experience as a Data Engineer, preferably in pharma, biotech, or healthcare.
Proficiency in Python, SQL, and cloud data services such as Snowflake, Redshift, or BigQuery.
Familiarity with NoSQL and relational databases and streaming tools like Kafka.
Experience with metadata management, data governance, and security practices.
Strong collaboration and communication skills to work across business and technical teams.
Nice to Have
Experience with ML pipelines and AI integration.
Knowledge of CDISC, SDTM, or other clinical data standards.
Exposure to DevOps, Docker, or Kubernetes.