Data Engineering Manager - Data Services

Hyderabad (Office)

Novartis

Working together, we can reimagine medicine to improve and extend people’s lives.

View company page

Job Description Summary

• Bring deep domain understanding in at least one of the following areas – a) Pharma R&D, b) Manufacturing, Procurement and Supply Chain and c) Marketing and Sales. Experience in working in Pharma / Life Science industry strongly preferred
• Collaborate with business stakeholders, data scientists and IT teams to create and implement world class data products and solutions
• Can act as a hands-on engineer in curating data, onboarding data assets to the FAIRification process and managing data quality and standards
• Brings strong understanding of enterprise approved schema, tools and platforms and can leverage them to deliver high quality clean and linked data across projects
• Manage quality and consistency of NBS CONEXTS data services delivery to all stakeholders
• Ensure compliance with GMP and regulatory requirements and continuous improvement of quality relevant processes within area of responsibility
• Deliver on data strategy priorities and DLC activities in an AGILE manner with appropriate documentation and communication throughout the delivery of services


 

Job Description

Data Engineering Manager

Location – Hyderabad #LI Hybrid  
 
About the Role: 

Act as a technical expert in data engineering & management to the team. Collaborate with business partners, data scientists and IT teams to create and implement world class data products and solutions. Act as a hands-on engineer in curating data, onboarding data assets to the FAIRification process and managing data quality and standards. 

Manage quality and consistency of NBS CONEXTS data services delivery to all collaborators. Deliver on data strategy priorities and DLC activities in an AGILE manner with appropriate documentation and communication throughout the delivery of services. 

Key Responsibilities: 

  • Bring deep domain understanding in Commercial operations, Sales & Marketing. Experience in working in Pharma / Life Science industry is strongly preferred 
  • Collaborate with business partners, data scientists and IT teams to create and implement world class data products and solutions 
  • Can act as a hands-on engineer in curating data, onboarding data assets to the FAIRification process and managing data quality and standards 
  • Brings good understanding of enterprise approved schema, tools and platforms and can use them to deliver high quality clean and linked data across projects 
  • Manage quality and consistency of NBS CONEXTS data services delivery to all partners 
  • Ensure compliance with GMP and regulatory requirements and continuous improvement of quality relevant processes within area of responsibility 
  • Deliver on data strategy priorities and DLC activities in an AGILE manner with appropriate documentation and communication throughout the delivery of services. 

Essential Requirements: 

  • Masters/ PhD in Computer Sciences / IT or other quantitative sciences 
  • 7+ years’ experience in a Global company as a data steward, engineer, modeler or data scientist 
  • Business understanding of pharmaceutical industry and data standards. Domain experience in at least one of the following areas – a) Pharma R&D, b) Manufacturing, Procurement and Supply Chain and c) Marketing and Sales. Experience in working in Pharma / Life Science industry and US healthcare data is strongly preferred. 
  • Understanding of data modeling (conceptual, logical, and physical) using different data modeling methodologies, understanding of semantic modeling techniques and graph databases 
  • Experience on data wrangling including Ingestion, Unification, Anonymization, Search, Master & Meta Data Management and Governance. 

Desirable requirements: 

  • Hand on experience in working with ETL process, and programming/scripting skills (Python) for data preparation and analysis. Experience in Master Data Management and data quality controls is a must. 
  • Good communication and presentation skills with consulting and senior partners engagement experience. Experience in Scrum Methodology is a plus. Foundational understanding of big data ecosystem, knowledge of AWS, AZURE Stack and basics of NLP would be an advantage 

Why Novartis: Our purpose is to reimagine medicine to improve and extend people’s lives and our vision is to become the most valued and trusted medicines company in the world. How can we achieve this? With our people. It is our associates that drive us each day to reach our ambitions. Be a part of this mission and join us! Learn more here: https://www.novartis.com/about/strategy/people-and-culture 
 
You’ll receive: You can find everything you need to know about our benefits and rewards in the Novartis Life Handbook. https://www.novartis.com/careers/benefits-rewards 

Commitment to Diversity and Inclusion:  

Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve. 


Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to hear more about Novartis and our career opportunities, join the Novartis Network here: https://talentnetwork.novartis.com/network


 

Skills Desired

Agility, Analytical Thinking, Brand Awareness, Building Construction, Business Analytics, Cross-Functional Collaboration, Digital Marketing, Marketing Strategy, Media Campaigns, Project Management, Sales, Stakeholder Engagement, Stakeholder Management, Strategic Marketing
Apply now Apply later
  • Share this job via
  • or

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Job stats:  4  0  0

Tags: Agile AWS Azure Big Data Business Analytics Consulting Data management Data quality Data strategy Engineering ETL NLP Pharma PhD Python R R&D Scrum

Perks/benefits: Team events

Region: Asia/Pacific
Country: India

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.