[Hiring] Data Architect @UnitedHealth Group

Role Description

We are seeking a Data Architect / Data Engineering Lead to own the end-to-end architecture and engineering standards for modern data platforms. This role partners closely with product, analytics, and engineering teams to design scalable, secure, and cost-effective data solutions - while remaining hands-on with implementation where it matters most. This position blends data architecture leadership with data engineering execution, ensuring data is delivered reliably and with high quality.

• Define and evolve target-state data architecture, including reference architectures, integration patterns, and platform standards across warehouse/lakehouse ecosystems.
• Lead architectural decision-making for cloud data platforms (e.g., Snowflake, Databricks) including compute/storage patterns, multi-environment strategies, security boundaries, and cost controls.
• Create technical roadmaps that align business outcomes with scalable data capabilities (analytics, operational reporting, AI/ML readiness).
• Own enterprise and domain data modeling standards (conceptual/logical/physical), including dimensional modeling, canonical models, and patterns for curated datasets.
• Ensure consistent definitions, metrics alignment, and high-quality, analytics-ready data products.
• Lead design and build of robust ELT/ETL pipelines using Python and distributed processing (Spark) as needed.
• Drive performance tuning and optimization across pipelines and data platforms (query patterns, clustering/partitioning, incremental loads, caching strategies).
• Establish engineering practices that improve reliability, maintainability, and developer productivity.
• Design and operationalize workflow orchestration using Apache Airflow, including DAG standards, scheduling patterns, dependency management, retries, SLAs, and backfills.
• Implement and manage Airflow runtime patterns in managed platforms such as Astronomer (or equivalent), including environment promotion strategies and operational readiness.
• Define and implement data quality frameworks (validation checks, anomaly detection, reconciliation, data contracts) and operational monitoring.
• Partner with governance/security stakeholders to ensure compliant data handling, access controls, lineage, metadata, and auditability.
• Lead/mentor engineers and architects through design reviews, code reviews, and architecture governance forums; raise the bar on engineering excellence.
• Translate complex technical concepts into clear guidance for stakeholders; drive alignment on tradeoffs, timelines, and expected outcomes.

Qualifications

• 8+ years in data engineering and/or data architecture roles with demonstrated ownership of enterprise-scale data solutions.
• 6+ years of data architecture experience: designing modern data platforms, integration patterns, and scalable data delivery approaches.
• 3+ years of data modeling expertise (dimensional, normalized, canonical models; conceptual/logical/physical modeling).
• 3+ years of proficiency with Python and SQL; solid engineering discipline (testing, documentation, maintainability).
• 1+ years of experience with cloud data technologies including Snowflake and/or Databricks (Spark-based engineering).
• 1+ years of workflow orchestration experience with Apache Airflow; experience with managed Airflow platforms such as Astronomer.
• 1+ years of experience implementing production-grade pipelines (batch and/or streaming), including CI/CD practices, environment promotion, and operational support.
• 1+ years of experience leading technical direction, mentoring engineers, and influencing architecture decisions across teams.

Preferred Qualifications

• Bachelor’s degree in Information Technology, Computer Science or related field.
• dbt experience (modeling and transformation lifecycle management).
• Experience with Snowpark framework.
• Experience with data governance/metadata tools and practices (catalog, lineage, access policies).
• Observability tooling experience (pipeline monitoring, alerting, logging, operational dashboards).
• Infrastructure-as-code and containerization (Terraform, Docker, Kubernetes) in support of data platforms.
• Experience supporting regulated data environments (e.g., healthcare/PII/PHI) and security-by-design patterns.

Benefits

• A comprehensive benefits package.
• Incentive and recognition programs.
• Equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements).

Application Deadline

This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.