Senior Data Engineer

This is an Analytics Engineering role that will join the team as a Senior Data Engineer focused on building Mayo Clinic’s IAM Data Fabric, a single, trusted source of identity data that the rest of our Identity and Access Management system is built upon. The Fabric brings identity, account, entitlement, access, ownership, and risk data from across the enterprise into one place, giving Mayo Clinic a comprehensive view of who has access to what, how it was granted, and where risk is concentrated. Access certifications, audit evidence, lifecycle automation, and executive reporting all depend on it.

In this role, your primary focus will be the Fabric’s reporting and analytics layer: designing BigQuery data products and Power BI semantic models that turn identity data into clear, actionable insight for IAM leadership, application owners, Information Security, and Audit. You will partner closely with teams across the Identity Management Program to understand their questions, model the data to answer them, and establish reporting standards the broader program can rely on. Over time, you will expand into the ingestion pipelines and foundational platform components that feed the Fabric, so curiosity about how data moves from source to report and a willingness to learn ETL and platform engineering will be required. You will work hands-on with Google Cloud, BigQuery, Dataform or dbt, Power BI, Cosmos DB and AI coding assistants such as Claude and Codex, on a small, senior team where your work directly shapes how Mayo Clinic understands and secures identity.

Develops and deploys data pipelines, integrations and transformations to support analytics and machine learning applications and solutions as part of an assigned product team using various open-source programming languages and vended software to meet the desired design functionality for products and programs. The position requires maintaining an understanding of the organization's current solutions, coding languages, tools, and regularly requires the application of independent judgment. May provide consultative services to departments/divisions and leadership committees. Demonstrated experience in designing, building, and installing data systems and how they are applied to the Department of Data & Analytics technology framework is required. Candidate will partner with product owners and Analytics and Machine Learning delivery teams to identify and retrieve data, conduct exploratory analysis, pipeline and transform data to help identify and visualize trends, build and validate analytical models, and translate qualitative and quantitative assessments into actionable insights.

This vacancy is not eligible for sponsorship/ we will not sponsor or transfer visas for this position. Also, Mayo Clinic DOES NOT participate in the F-1 STEM OPT extension program.

A Bachelor's degree in a relevant field such as engineering, mathematics, computer science, information technology, health science, or other analytical/quantitative field and a minimum of five years of professional or research experience in data visualization, data engineering, analytical modeling techniques; OR an Associate’s degree in a relevant field such as engineering, mathematics, computer science, information technology, health science, or other analytical/quantitative field and a minimum of seven years of professional or research experience in data visualization, data engineering, analytical modeling techniques. In-depth business or practice knowledge will also be considered.

• 5+ years of hands-on experience in analytics engineering, data engineering, or BI development
• Expert-level SQL, including complex joins, window functions, CTEs, and performance tuning on large analytical datasets.
• Proficiency in Python for data transformation and automation.
• 2+ years of production experience with Google BigQuery (partitioning, clustering, cost/slot optimization, scheduled queries, authorized views)
• Hands-on experience building and maintaining transformation pipelines with Dataform or dbt (modular SQL models, dependency management, testing, documentation, and scheduled runs) using Git-based source control and CI/CD for data assets.
• Working knowledge of GCP services (IAM, Cloud Storage, Dataflow, Pub/Sub, Managed Airflow).
• Experience building and maintaining Power BI reports and semantic models, including DAX, row-level security, and dataset refresh/gateway management, with governed, documented metric definitions that serve as a single source of truth for key KPIs
• Demonstrated experience applying dimensional modeling, data warehousing concepts, and data quality practices.
• Demonstrated ability to translate ambiguous analytic and reporting requests into well-defined data products
• Experience leading technical design reviews or establishing engineering and reporting standards for a team.

Preferred Qualifications

• Experience with a metrics or semantic layer tool (Looker/LookML, dbt Semantic Layer/MetricFlow, or Dataform-based metric definitions), including Looker Studio alongside Power BI
• Exposure to identity, security, or compliance datasets and their governance requirements (PHI/PII handling, HIPAA, least-privilege access), or experience in healthcare or another regulated industry
• Experience with NoSQL/document databases, particularly Azure Cosmos DB (partition key design, RU consumption, change feed)
• Experience with data observability and testing frameworks (Great Expectations, Monte Carlo, or similar) beyond native Dataform/dbt tests
• Hands-on experience with agentic AI workflows, MCP-based tool integrations, or building LLM-assisted data tooling
• Familiarity with cross-cloud integration (Azure Data Factory, Synapse, or Microsoft Fabric) and infrastructure-as-code (Terraform) for GCP and Azure
• Familiarity with Agile/SAFe delivery, Azure DevOps or Jira.

Certifications strongly encouraged

• dbt Analytics Engineering Certification
• Google Cloud Professional Data Engineer
• Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
• Microsoft Certified: Power BI Data Analyst Associate (PL-300)