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Tech Stack
Tools & technologiesAWSAzureCloudETLNoSQLPandasPythonSparkSQL
About the role
Key responsibilities & impact- Design, build, and maintain robust ETL/ELT pipelines supporting large, complex datasets with evolving schemas
- Support embedding generation and vector-based data pipelines for AI and GenAI use cases
- Develop scalable batch and streaming data pipelines using cloud-based data platforms (e.g., Snowflake or Databricks)
- Create and evolve semantic data models that transform raw data into analytics-ready, trustworthy datasets
- Build data preprocessing, validation, and quality-assurance tooling to ensure reliability and correctness
- Design pipelines that support both offline model training and low-latency inference workloads
- Drive the design of modern data architectures that balance scalability, performance, and maintainability
- Implement data quality checks, lineage, and monitoring for enterprise-scale datasets
- Work closely with product, analytics, AI/ML, IT, and business teams to understand data needs and enable data-driven initiatives
- Interface with stakeholders across manufacturing, quality, post-market surveillance, commercial, and clinical domains
- Provide technical leadership and mentorship to other data engineers, promoting best practices and continuous improvement
Requirements
What you’ll need- Bachelor’s Degree or higher in Computer Science, Mathematics, engineering or a related technical field AND 6-8 years of job related experience OR High School Diploma/GED from AND 10 years of the same job-related experience
- Strong experience with SQL, relational and NoSQL databases
- Hands-on experience building and maintaining large-scale data pipelines in cloud environments (Azure or AWS)
- Experience with Databricks or Snowflake and distributed data processing frameworks (e.g., Spark)
- Familiarity with feature stores, vector databases, or model-adjacent data systems
- Experience managing data quality, validation, and lineage for large, complex datasets
- Proficiency in Python and experience with data-frame libraries (e.g., Pandas, Polars)
- Experience with ETL/workflow orchestration tools (e.g., Databricks Workflows, Azure Data Factory, AWS Glue)
- Familiarity with common data formats (CSV, JSON, XML, Parquet, etc.)
- Strong communication skills with the ability to explain technical concepts to non-technical stakeholders
- Professional proficiency in English, with regular collaboration across global team
- Additional qualifications that could help you succeed even further in this role include:
- Experience in healthcare, medical device, life sciences, or manufacturing environments
- Familiarity with Business Intelligence tools and analytics platforms
- Experience supporting AI/ML use cases through high-quality, well-modeled data
- Knowledge of data privacy, security, and compliance best practices
- In this role, you may be required to enter healthcare or other third-party facilities. Those facilities may, in turn, require you to possess certain licenses, vaccinations, and/or other credentials or qualifications (collectively “prerequisites to entry”) for regulatory, safety, or other business reasons.
Benefits
Comp & perks- Supporting Your Well-being
- Solventum offers many programs to help you live your best life – both physically and financially.
- To ensure competitive pay and benefits, Solventum regularly benchmarks with other companies that are comparable in size and scope.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
ETL/ELT Pipeline DevelopmentSQLPythonData Quality ChecksData ValidationData Lineage ManagementDistributed Data Processing (Spark)Data-Frame Libraries (Pandas, Polars)Cloud Environments (Azure, AWS)Data Formats (CSV, JSON, XML, Parquet)
Soft Skills
Strong Communication SkillsTechnical LeadershipMentorship
