Role at a glance
- Job function
-
AI & Data Data Engineering MLOps & ML Infrastructure
- Salary
- Not Disclosed
- Location
- Bangalore, India
- Work arrangement
- Hybrid
- Employment
- Full-time
- Experience
- 10+ years of overall experience with 7+ years focused on delivering enterprise-scale data engineering solutions.
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Role Summary
The Staff Data Engineer joins Thermo Fisher Scientific’s Automation, AI and Data team in Bangalore, delivering data engineering pipelines and solutions through the Enterprise Data Platform for various groups and divisions. The role supports data, analytics, AI, and Generative AI use cases while helping strengthen enterprise data engineering capabilities.
What You'll Do
- Convert business requirements into scalable data engineering and GenAI-ready pipelines with functional analysts.
- Build, test, and optimize data pipelines and feature stores for real-time, batch processing, and Generative AI/ML workloads.
- Support the evolution of Enterprise Data Platform architecture and participate in roadmap activities.
- Collaborate with leadership and partners to ensure high-quality, governed data across DWH, AWS, and AI/ML consumption layers.
- Provide hands-on technical guidance and oversight across multiple data and AI-driven projects.
- Identify data quality, model input, and AI output risks and work with partners to define mitigation strategies.
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View full postingQualifications
10+ years of overall experience, including 7+ years delivering enterprise-scale data engineering solutions; 5+ years building cloud-based data and BI solutions on AWS; 5+ years programming in SQL, PySpark, and Python; experience with data modeling, data pipelines, distributed data processing, Generative AI or ML-enabled solutions, RAG patterns, embeddings, vector stores, feature stores, MLOps/LLMOps, Agile, DevOps, DataOps, and DevSecOps.
Required
- 5+ years of proven experience building Cloud-based data and BI solutions on AWS
- Strong hands-on experience with data modeling, data pipelines, and large-scale distributed data processing
- 5+ years of programming experience in SQL, PySpark, and Python
- Preparing, curating, and optimizing data for LLMs and ML models
- Supporting RAG (Retrieval-Augmented Generation) patterns, embeddings, vector stores, or feature stores
- Familiarity with AI/ML lifecycle practices, including MLOps/LLMOps, model integration, and production deployment considerations
- Experience with Agile delivery models, following DevOps, DataOps, and DevSecOps practices
Original job description
Content provided by the employer
Original job description
Content provided by the employer
Work Schedule
Standard (Mon-Fri)Environmental Conditions
OfficeJob Description
Job Title – Staff Data Engineer
Job Location : Bangalore, India
About Company:
Thermo Fisher Scientific Inc. is the world leader in serving science, with revenues of more than $40 billion and approximately 1,20,000 employees globally. Our Mission is to enable our customers to make the world healthier, cleaner, and safer. We help our customers accelerate life sciences research, solve complex analytical challenges, improve patient diagnostics, deliver medicines to market and increase laboratory productivity.
About Team: We are Automation, AI and Data (AAD) team that caters to data engineering and analytics, automation and AI solutions for various groups and divisions within Thermofisher Scientific.
What will you do?
As a staff data engineer, you will play a key role in strengthening our data engineering capabilities delivering data engineering pipelines and solutions through Enterprise Data Platform (EDP) for various groups and divisions.
General Job Functions
- Collaborate with functional analysts to convert business requirements into scalable data engineering and GenAI-ready pipelines.
- Collaborate with the Scrum Master on product backlogs and support sprint planning and delivery.
- Build, test, and optimize data pipelines and feature stores for various use cases, including real-time, batch processing, and Generative AI/ML workloads.
- Support the evolution of Enterprise Data Platform (EDP) architecture and participate in roadmap activities related to data, analytics, and AI platform initiatives.
- Collaborate with leadership and partners to ensure high-quality, governed data across DWH, AWS, and AI/ML consumption layers for BI, analytics, and GenAI use cases.
- Provide hands-on technical guidance and oversight across multiple data and AI-driven projects.
- Identify potential risks related to data quality, model inputs, and AI outputs, and work with partners to define mitigation strategies.
- Actively support and contribute to development activities in data engineering and GenAI enablement, ensuring bandwidth and technical direction when needed.
- Implement and follow Agile development methodologies, adhering to DevOps, DataOps, and MLOps/LLMOps best practices.
- Ensure teams follow prescribed development processes, coding standards, and architectural patterns.
Must have skills and experience
- 10+ years of overall experience with 7+ years focused on delivering enterprise-scale data engineering solutions.
- 5+ years of proven experience building Cloud-based data and BI solutions on AWS.
- Strong hands-on experience with data modeling, data pipelines, and large-scale distributed data processing.
- 5+ years of programming experience in SQL, PySpark, and Python.
- Experience working with Generative AI or ML-enabled solutions, including:
- Preparing, curating, and optimizing data for LLMs and ML models
- Supporting RAG (Retrieval-Augmented Generation) patterns, embeddings, vector stores, or feature stores
- Familiarity with AI/ML lifecycle practices, including MLOps/LLMOps, model integration, and production deployment considerations.
- Experience with Agile delivery models, following DevOps, DataOps, and DevSecOps practices.
- Excellent written, verbal, interpersonal, and partner communication skills.
- Strong analytical skills with the ability to translate business requirements into data and AI-ready technical solutions.
- Ability to work effectively with cross-functional, globally distributed teams using multiple communication channels (Email, MS Teams, meetings).
- Excellent prioritization, problem-solving, and decision-making skills.
Our Mission is to enable our customers to make the world healthier, cleaner, and safer. Watch as our colleagues explain 5 reasons to work with us. As one team of 1,20,000 colleagues, we share a common set of values - Integrity, Intensity, Innovation and Involvement - working together to accelerate research, solve complex scientific challenges, drive technological innovation and support patients in need.
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.
About the company
Thermo Fisher Scientific
Large Enterprise
Thermo Fisher Scientific is a global leader in serving science, providing a wide range of analytical instruments, reagents, and software solutions for healthcare, pharmaceuticals, and life sciences research. With a commitment to innovation and quality, the company enables customers to make significant advancements in scientific discovery and healthcare diagnostics. Thermo Fisher operates in more than 50 countries and employs over 80,000 people, fostering a collaborative environment aimed at enhancing global health and safety. Through its broad portfolio of brands and technologies, the company plays a vital role in accelerating life-changing research and improving patient outcomes worldwide.