Lead Semantic Data Engineer
MSD (Merck & Co., Inc.) (company site, opens in a new tab)HybridDirect career pageEst. 30–55 LPA
Posted on 8 Sept
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Reach people at MSD (Merck & Co., Inc.)
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at MSD (Merck & Co., Inc.) you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead design and implementation of scalable knowledge graph architectures integrating diverse scientific datasets in pharmaceutical research.
- Drive adoption and governance of graph technologies and platforms such as RDF, SPARQL, Amazon Neptune within enterprise-scale environments.
- Collaborate with cross-functional teams to translate business needs into semantic data models and mentor engineers on ontology and graph engineering best practices.
Minimum Requirements
- Experience with semantic web technologies including RDF and SPARQL.
- Proficiency in Amazon Web Services, especially serverless services like Lambda and Step Functions.
- Strong data engineering skills including SQL, ETL, and programming in Python.
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Deep expertise in knowledge graph architecture, ontology engineering, and graph database technologies within pharmaceutical R&D context.
- Experience with DevSecOps practices including CI/CD, Git, infrastructure-as-code (CloudFormation/Terraform), and containerization (Docker).
- Ability to lead cross-team collaboration and mentor engineering teams in semantic data engineering and graph technology adoption.