Note: The job is a remote job and is open to candidates in USA. Optum is a global organization that delivers care aided by technology to help millions of people live healthier lives. The Senior Data Engineer will lead enterprise data architecture, modeling, platform implementation, governance, security, automation, and reliability initiatives while partnering with cross-functional teams and mentoring technical staff. The role will also design and deploy responsible AI-powered solutions to address complex business challenges.
Responsibilities
- Define and own the end‑to‑end enterprise data architecture ensuring scalability, performance, integration, and long‑term sustainability
- Develop and maintain reference architectures, patterns, and standards for data modeling, storage, ingestion, processing, governance, and consumption
- Align data platforms with business outcomes, regulatory requirements, cloud strategy, and modernization initiatives
- Evaluate and recommend technologies across SQL/NoSQL databases, data lakes, lake houses, ETL/ELT tools, and compute engines based on enterprise fit
- Lead the design of conceptual, logical, and physical data models to support OLTP, OLAP, streaming, and AI workloads. Architect robust database schemas, partition strategies, indexing policies, sharding methods, and storage optimizations
- Define standards for naming, modeling conventions, normalization/denormalization, and lifecycle management of data assets
- Provide expert guidance on SQL Server, SQL MI, Azure SQL, PostgreSQL, MongoDB, and other enterprise data platforms
- Architect and implement cloud-native, hybrid, and on-prem data platforms supporting ingestion, storage, processing, and analytics
- Design lake house and warehouse environments using Databricks, Synapse, ADF, Delta Lake, and scalable compute layers
- Build end-to-end data flows covering batch, streaming, ELT pipelines, metadata, lineage, and monitoring
- Ensure data platforms meet performance, concurrency, high-availability, and disaster recovery requirements
- Define policies for metadata management, classification, lineage, quality scoring, and stewardship
- Enable enterprise governance across catalogs, glossaries, access patterns, and regulatory compliance
- Enforce security controls such as RBAC, encryption, auditing, masking, and network isolation
- Establish data quality standards including validation rules, anomaly detection, and reconciliation workflows
- Implement infrastructure and data platform provisioning using Terraform/IaC for repeatable deployments
- Build CI/CD pipelines (GitHub Actions, Azure DevOps) for data models, SQL objects, ETL workflows, and platform components
- Support containerized workloads using Docker and Kubernetes/AKS
- Automate environment setup, schema migrations, monitoring, and compliance checks
- Define performance benchmarks and baselines across storage, computer, SQL, and data movement
- Optimize SQL/ETL workloads, reduce infrastructure costs, and tune pipelines for high throughput
- Establish monitoring, alerting, anomaly detection, and reliability playbooks
- Lead incident triage, RCA, and long-term remediation for platform stability
- Partner with Product, Engineering, Analytics, Security, and Cloud teams to align data strategy with business goals
- Translate business requirements into scalable data solutions
- Provide mentorship and technical leadership to data engineers, DBAs, and architects
- Stay current with emerging trends in data modeling, platforms, storage formats, and distributed systems
- Drive modernization initiatives such as lake house adoption, automation, and cloud-native architecture
- Refine architecture based on usage insights and business evolution
- Maintain documentation of architectures, data flows, ER diagrams, standards, and decisions
- Conduct reviews, design sessions, and best-practice workshops
- Promote organization-wide literacy on governance, modeling, and quality
- Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI
Skills
- • Bachelor's degree in Computer Science, Information Systems, or IT related field
- • 7+ years of experience in data modeling, database design, and data architecture patterns
- • 7+ years of experience with SQL Server, SQL MI, Azure SQL, PostgreSQL, MongoDB
- • 7+ years of experience in performance tuning, indexing, partitioning, and workload optimization
- • 7+ years of experience with Metadata, lineage, quality, RBAC, encryption, masking, compliance
- • 4+ years of experience with Azure Databricks, Synapse, ADF
- • 4+ years of experience with Terraform, GitHub Actions, DevOps, Kubernetes/AK
- • Strong analytical, communication, and leadership skills
Benefits
- Flexibility to telecommute from anywhere within the U.S.
- Comprehensive benefits package, subject to eligibility requirements
- Incentive and recognition programs, subject to eligibility requirements
- Equity stock purchase, subject to eligibility requirements
- 401k contribution, subject to eligibility requirements
- Career development opportunities
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