Senior Data Engineering Consultant
unitedhealthgroup
Job Description
- Data Engineering and Architecture
- Design and build scalable, secure, and high-performance data platforms on Microsoft Azure
- Develop batch and real-time data pipelines using Databricks, Spark, and Azure Data Factory
- Implement Medallion Architecture (Bronze, Silver, Gold) and Lakehouse design patterns
- Optimize data processing workflows for performance, cost, reliability, and scalability
- Build enterprise data models supporting analytics, AI/ML, and reporting use cases
- Azure and Databricks
- Develop and maintain solutions using Azure Data Lake, Azure Databricks, Azure Synapse, Event Hub, and Azure SQL
- Leverage PySpark, Spark SQL, Delta Lake, and Databricks Workflows for large-scale data processing
- Implement monitoring, performance tuning, and governance within Azure environments
- Support cloud migration and modernization initiatives
- Generative AI and LLM Enablement
- Build AI-ready data pipelines to support LLM, RAG, and Agentic AI solutions
- Integrate vector databases, embeddings, semantic search, and knowledge retrieval frameworks
- Collaborate with Data Scientists and AI Engineers to develop GenAI applications
- Ensure data quality, lineage, governance, and compliance for AI workloads
- Support LLM operationalization and production deployment
- CI/CD, DataOps and MLOps
- Design and implement CI/CD pipelines using Azure DevOps and GitHub Actions
- Automate deployment of data engineering artifacts, notebooks, workflows, and infrastructure
- Implement Infrastructure as Code (Terraform/Bicep)
- Establish DataOps best practices for version control, testing, release management, and monitoring
- Enable automated testing, quality validation, and deployment governance
- Collaboration and Leadership
- Partner with business stakeholders, architects, AI/ML teams, and product owners
- Mentor junior engineers and promote engineering best practices
- Contribute to architecture reviews, technology roadmaps, and innovation initiatives
- Drive adoption of enterprise data governance, security, and Responsible AI standards
- AI Builder Responsibilities:
- Design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms, translating business needs into scalable applications that enhance products, workflows, and decision-making
- 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
- Design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms, translating business needs into scalable applications that enhance products, workflows, and decision-making