Cloud Data Architect & Engineering Lead

Taleo; Minnetonka (MN); On-site; USD 113,000 - 193,000; Full time

Job summary

UnitedHealth Group is seeking a Data Architect / Data Engineering Lead to own end-to-end data platforms, partnering with product, analytics and engineering teams to design scalable, secure, and cost-effective solutions. You will lead architecture roadmaps and govern patterns while staying hands-on with pipelines and modeling.

Responsibilities cover cloud platforms (Snowflake, Databricks), ELT/ETL with Python and Spark, Airflow workflows, data quality and governance.

Qualifications

• 8+ years in data engineering/architecture owning enterprise-scale data solutions.
• 6+ years designing modern data platforms and scalable data delivery approaches.
• 3+ years of data modeling expertise (dimensional, canonical models; conceptual/logical/physical).
• 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.

Responsibilities

• Define and evolve target-state data architecture, including reference architectures 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.

Skills

Data architecture leadership

Python

SQL

Spark

Airflow

Snowflake

Databricks

Data modeling

Data governance

Cloud data platforms

Education

Bachelor’s degree in IT/CS or related field

Tools

Snowflake

Databricks

Apache Airflow

Astronomer

Spark

Terraform

Docker

Kubernetes

Job description

UnitedHealth Group is seeking a Data Architect / Data Engineering Lead to own end-to-end data platforms, partnering with product, analytics and engineering teams to design scalable, secure, and cost-effective solutions. You will lead architecture roadmaps and govern patterns while staying hands-on with pipelines and modeling.

Responsibilities cover cloud platforms (Snowflake, Databricks), ELT/ETL with Python and Spark, Airflow workflows, data quality and governance.