1 month ago
Bengaluru, IndiaSenior
Responsibilities
- Design, build, and maintain ETL/ELT pipelines for large, complex datasets with evolving schemas.
- Develop batch and streaming data pipelines using cloud-based data platforms.
- Support embedding generation and vector-based data pipelines for AI and GenAI use cases.
- Create semantic data models that transform raw data into analytics-ready datasets.
- Build data preprocessing, validation, and quality-assurance tooling.
- 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 datasets.
- Collaborate with product, analytics, AI/ML, IT, and business teams to support data-driven initiatives.
- Work with stakeholders across manufacturing, quality, post-market surveillance, commercial, and clinical domains.
- Provide technical leadership and mentorship to other data engineers.
Requirements
- Bachelor’s degree or higher in computer science, mathematics, engineering, or a related technical field and 6–8 years of job-related experience, or a high school diploma/GED and 10 years of the same experience.
- Strong experience with SQL and relational and NoSQL databases.
- Hands-on experience building and maintaining large-scale data pipelines in Azure or AWS cloud environments.
- 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 large, complex datasets.
- Proficiency in Python and experience with data-frame libraries such as Pandas or Polars.
- Experience with ETL and 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 for explaining technical concepts to non-technical stakeholders.
- Professional proficiency in English and ability to collaborate across global teams.
- Healthcare, medical device, life sciences, or manufacturing experience is preferred.
- Familiarity with business intelligence tools and analytics platforms is preferred.
- Experience supporting AI/ML use cases with high-quality, well-modeled data is preferred.
- Knowledge of data privacy, security, and compliance best practices is preferred.
- May need to satisfy facility-specific licenses, vaccinations, or other entry credentials.
Benefits
- Hybrid work arrangement.
- May include up to 20% domestic travel.
- Solventum offers programs supporting physical and financial well-being.
- Competitive pay and benefits are benchmarked against comparable companies.
Tech Stack
Categories
Data Engineering