Manager, Data Engineering

We are looking for a Manager, Data Engineering, who will lead teams responsible for building, scaling, and operating enterprise-grade data architectures, including data lakes, data warehouses, and lakehouse platforms, that power Clarivates AI- and analytics-driven products. We are building the next generation of AI-powered analytics, insights, and decision-support platforms for the global Life Sciences and Healthcare (LSH) community.

These Product platforms enable mission-critical use cases such as drug discovery acceleration, treatment effectiveness analysis, real-world evidence generation, and patient journey insights. This role blends technical leadership, data architecture expertise, dimensional modeling, and people management.

You will guide teams in delivering robust data pipelines, analytical data models (star and snowflake schemas), analytics-ready datasets, and AI-enabled data foundations, while collaborating closely with product managers, architects, data scientists, and platform engineering teams.

If youre excited to work at the intersection of data engineering, data architecture, analytics, and AIand to power products that accelerate scientific discovery and improve patient outcomesClarivate is the place for you.

About You experience, education, skills, and accomplishments

• Bachelors or Masters degree in Computer Science, Data Science, Engineering, Analytics, or a related field.
• Minimum 10+ years of experience in data engineering, analytics engineering, or data-intensive software engineering
• Minimum 2+ years of people management or technical leadership experience
• Strong experience designing enterprise data architectures, including data lakes, data warehouses, and/or lakehouse platforms
• Proven expertise in dimensional data modeling (star schema, fact/dimension tables) for analytics and BI
• Experience building or supporting analytics- or AI-enabled data platforms
• Exposure to US Healthcare data such as claims, clinical data, payer/provider systems, or real-world evidence
• Hands-on experience with cloud platforms (AWS, Azure, or GCP)
• Strong proficiency in SQL and working knowledge of Python or ETL Tools
• Bachelors or masters degree in computer science, Data Science, Engineering, Analytics, or a related field

It would be great if you also had . . .

• Experience with Snowflake, Databricks, Spark, or similar data warehouse/lakehouse platforms
• Hands-on experience implementing enterprise data lakes and data warehouses at scale
• Exposure to ML pipelines, MLOps, or close collaboration with data science teams
• Familiarity with GenAI, LLMs, vector databases, or emerging AI-driven data architectures
• Experience working in regulated healthcare or life sciences environments

What would you be doing in this role:

Data Architecture & Platform Engineering

• Lead the design and evolution of scalable data architectures, including data lakes, data warehouses, and lakehouse platforms
• Define architectural patterns for batch, streaming, and real-time data processing
• Ensure platforms are optimized for performance, scalability, cost efficiency, reliability, and security
• Partner with enterprise and solution architects to align data architecture with long-term platform strategy
• Data Engineering & Analytical Modeling
• Lead the development and operation of scalable, reliable data pipelines supporting analytics and AI use cases
• Design, govern, and review dimensional data models, including fact and dimension tables, star and snowflake schemas
• Establish best practices for data ingestion, transformation, modeling, and query optimization
• Enable self-service analytics and BI through well-structured, high-quality analytical datasets

AI & Analytics Enablement

• Partner with data science and ML teams to productionize AI/ML models using robust data pipelines
• Enable consistent metrics and KPIs by delivering trusted analytical layers on top of data lake and warehouse platforms
• Translate product and business requirements into scalable analytical and architectural data solutions
• Data Quality, Governance & Compliance
• Champion data quality, observability, consistency, and metric integrity across platforms
• Ensure data architecture and engineering practices meet healthcare-grade security, governance, and compliance requirements
• Implement and support data lineage, auditability, and traceability across lakes, warehouses, and analytical layers

Leadership & Delivery Excellence

• Manage, mentor, and develop a team of data engineers and analytics engineers
• Drive sprint planning, execution, and predictable delivery in partnership with product and engineering leadership
• Participate in hiring, onboarding, coaching, and performance management to build high-performing teams

Innovation & Cross-Functional Collaboration

• Introduce modern data engineering and architecture practices, including lakehouse patterns, automation, and real-time analytics
• Collaborate with product, architecture, data science, and platform teams to align roadmaps and priorities
• Communicate progress, risks, architectural trade-offs, and technical decisions clearly to stakeholders and senior leaders.

About the Team

You will join the Life Sciences & Healthcare Commercial Technology Product Engineering organization, focused on delivering data- and AI-powered product capabilities. The team is globally distributed across India and the U.S., working in a hybrid model.