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Tech Stack
Tools & technologiesETLMongoDBNoSQLPostgres
About the role
Key responsibilities & impact- Design and scale Retrieval-Augmented Generation (RAG) pipelines
- Transform unstructured IT logs and documentation into optimized vector embeddings
- Maintain the health and performance of vector databases such as Pinecone, Milvus, or Weaviate
- Build knowledge graphs and semantic layers
- Develop automated data guardrails to detect noise, bias, and PII
- Identify and resolve data quality issues at the source
- Build, deploy, and maintain CI/CD pipelines for data infrastructure
- Ensure data context remains fresh and reliable
Requirements
What you’ll need- Expertise in data mining, data storage, and Extract-Transform-Load (ETL) processes
- Experience developing data pipelines and using tooling such as Glue, Databricks, Synapse, or Dataproc
- Experience with relational and NoSQL databases, including PostgreSQL, DB2, and MongoDB
- Excellent problem-solving, analytical, and critical thinking skills
- Ability to manage multiple projects simultaneously while maintaining attention to detail
- Ability to communicate with technical and non-technical colleagues and translate business needs into technical requirements
Benefits
Comp & perks- Flexible, supportive environment
- Well-being support through Be Well programs covering financial, mental, physical, and social health
- Dynamic, hybrid-friendly culture
- Personalized development goals and continuous feedback
- Access to cutting-edge learning opportunities
- Certifications with Microsoft, Google, and Amazon
- Coaching and hands-on experiences
- Career path and development tools