1 month ago
Bengaluru, IndiaSenior
Responsibilities
- Design, build, and maintain robust ETL/ELT pipelines for large and evolving datasets.
- Support embedding generation and vector-based data pipelines for AI and GenAI use cases.
- Develop scalable batch and streaming pipelines using cloud-based data platforms such as Snowflake or Databricks.
- Create semantic data models that transform raw data into analytics-ready datasets.
- Build preprocessing, validation, and quality-assurance tooling for reliable data.
- Design pipelines supporting offline model training and low-latency inference workloads.
- Drive scalable, performant, and maintainable data architecture designs.
- Implement data quality checks, lineage, and monitoring for enterprise-scale datasets.
- Collaborate with product, analytics, AI/ML, IT, business, and cross-functional domain stakeholders.
- Provide technical leadership and mentorship to other data engineers and promote engineering best practices.
Requirements
- Bachelor’s degree or higher in Computer Science, Mathematics, engineering, or a related technical field plus 6–8 years of job-related experience, or a high school diploma/GED plus 10 years of the same experience.
- Strong experience with SQL and relational and NoSQL databases.
- Hands-on experience building and maintaining large-scale cloud data pipelines in Azure or AWS.
- Experience with Databricks or Snowflake and distributed data processing frameworks such as Spark.
- Familiarity with feature stores, vector databases, or model-adjacent data systems.
- Experience managing data quality, validation, and lineage for complex datasets.
- Proficiency in Python and data-frame libraries such as Pandas or Polars.
- Experience with workflow orchestration tools such as Databricks Workflows, Azure Data Factory, or AWS Glue.
- Familiarity with CSV, JSON, XML, and Parquet data formats.
- Strong communication skills and the ability to explain technical concepts to non-technical stakeholders.
- Professional proficiency in English and ability to collaborate across global teams.
- Preferred experience includes healthcare, medical device, life sciences, or manufacturing environments; business intelligence tools; AI/ML data support; and data privacy, security, and compliance practices.
Benefits
- Hybrid work arrangement.
- Domestic travel may be required up to 20%.
- Solventum offers programs supporting physical and financial well-being.
- The role may require licenses, vaccinations, or other credentials for entry into healthcare or third-party facilities.
Tech Stack
Categories
Data Engineering
About Solventum
At Solventum, we enable better, smarter, safer healthcare to improve lives. We never stop solving for you.