N
Novartis
Data Engineer
Data Engineering Manager
On-siteSeniorData EngineerJust posted
Role summaryAI-generated
This role requires leading a team to architect and deploy high-performance data pipelines for healthcare analytics, ensuring seamless integration between cloud platforms and business intelligence tools. The manager will drive efficiency in data ingestion while fostering collaboration between engineering, data science, and commercial teams to deliver actionable insights.
Skills required
Cloud-based data integrationEtl pipelinesData pipeline orchestrationData quality frameworksScalable data architecturesCross-functional collaborationData warehouse optimizationAutomation scriptingData engineeringData scienceData qualityData pipelinesPythonCI/CDSparkETLDevOpsAWSSQLSnowflakePower BIData architectureData governanceData analyticsProject managementStakeholder management
About this role
Job Description Summary
As a Data Engineer Manager, you’ll lead the data engineering team and support the data science and/or reporting & analytics team inbuilding scalable Commercial solutions to enhance the medical/sales representative actionable. You’ll be at the forefront of cloud-based data integration, driving automation, quality, and efficiency while collaborating with cross-functional teams to deliver impactful insights. This is your opportunity to make a real difference in global healthcare through cutting-edge data engineering.Job Description
Major accountabilities:
- Design scalable data ingestion and integration solutions to support data products for data science and reporting & analytics.
- Ensure data quality by applying business and technical rules throughout its lifecycle.
- Identify and implement automation opportunities to streamline data processes.
- Build data pipelines using Python and CI/CD workflows for seamless data integration.
- Collaborate with solution architects and vendors to align with best practices.
- Apply data management principles including modelling, harmonization, and ontology standards.
- Manage metadata effectively and leverage enterprise ontology tools.
- Ensure adherence to FAIR data principles across applicable projects.
- Conduct feasibility assessments and define project requirements with stakeholders.
- Support end-user training and promote self-service data capabilities.
Minimum Requirements:
- University degree in Informatics, Computer Sciences, Life Sciences, or a related field.
- 7+ years of experience in data engineering with good understanding of healthcare or life sciences. Experience with Commercial is a plus.
- Proven expertise in Python, PySpark and R for ETL and BI data product development.
- Strong experience with DevOps, AWS cloud data integration and third-party ingestion tools.
- Proficiency in SQL for relational databases such as Oracle and MS SQL Server.
- Proficiency in Cloud based databases like Snowflake is a plus.
- Hands-on experience with ETL tools and BI platforms like Power BI.
- Solid understanding of data architecture, modelling, and analytics concepts.
- Familiarity with Agile methodologies in global project environments.
- Understanding of Data science concepts is a plus
Skills Desired
Clinical Data Management, Cross-Functional Team, Data Architecture, Data Governance, Data Management, Data Quality, Data Science, Data Strategy, Drug Development, Master Data, People Management, Agile/Scrum
Skills Desired
Analytical Thinking, Brand Awareness, Business Analytics, Cross-Functional Collaboration, Digital Marketing, Media Campaigns, Project Management, Project Planning, Sales, Stakeholder Engagement, Stakeholder Management, Waterfall ModelApply on Novartis →Opens in new tab
score your resume against this role
Similar open roles
SK
SponsoredLand 5x More Interviews - Resume & Strategy
CV ReviewLive One on One CallsStrategy
Book A Call ↗