Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.
Primary Responsibilities:
•Design, build, and optimize scalable batch, streaming, and near-real-time data pipelines across cloud and enterprise data platforms
•Develop AI-ready data products with solid focus on data quality, lineage, metadata, governance, observability, and reusability
•Build semantic and knowledge layers that define business meaning, entity relationships, ontology structures, and reusable context for AI agents and applications
•Implement GenAI data patterns including embeddings, vector search, semantic retrieval, RAG pipelines, hybrid search, and knowledge graph-based retrieval
•Work hands-on with Python, SQL, PySpark, Spark, Databricks, Snowflake, Kafka, and cloud-native data services
•Develop backend services, REST APIs, microservices, and data access layers using Python frameworks such as FastAPI, Flask, or equivalent
•Integrate structured and unstructured data sources into governed, searchable, and AI-consumable data products
•Build data interfaces that support analytics, ML models, GenAI applications, AI agents, and enterprise workflows
•Collaborate with AI/ML engineers, applied scientists, platform engineers, product teams, and business stakeholders to translate data needs into scalable technical solutions
•Ensure pipelines and data services are secure, reliable, observable, cost-efficient, and production-ready
•Apply CI/CD, testing, monitoring, logging, alerting, and operational best practices for data pipelines and API services
•Support enterprise standards for data governance, access control, privacy, compliance, and responsible AI usage
•Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
Required Qualifications:
•Graduate degree or equivalent experience
•8+ years of hands-on experience in data engineering, data platforms, backend engineering, or related roles
•Proven experience building ETL/ELT pipelines, data models, lakehouse patterns, and cloud-based data platforms
•Experience with Databricks, Snowflake, BigQuery, Azure Synapse, or similar modern data platforms
•Hands-on experience developing REST APIs, microservices, and backend data services using Python
•Experience working with structured, semi-structured, and unstructured data for analytics, ML, and GenAI use cases
•Experience with cloud platforms such as Azure, AWS, or GCP
•Practical exposure to GenAI data enablement including RAG, embeddings, semantic search, vector databases, and LLM-powered data workflows
•Solid hands-on expertise in Python, SQL, PySpark, Spark, and distributed data processing
•Solid understanding of data quality, lineage, metadata management, data catalogs, access controls, and observability
•Proven solid problem-solving, debugging, communication, and cross-functional collaboration skills
