Role Description Data Engineer gains access to data across the organization and provides ongoing analysis of the data by monitoring, profiling and analyzing databases. Requires a mix of functional, data and technical skills. The right candidate must be able to understand business requirements, translate them into information needs and implement those requirements using data available. The hire will be responsible for expanding and optimizing data architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems. The Data Engineer will support our software developers, database architects, and data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. - Assemble large, complex data sets that meet functional / non-functional business requirements. - Strong knowledge of SQL required. Ability to identify sets and subsets of information across multiple joins or unions of tables is preferred in addition to writing and troubleshooting SQL queries for data mining. - Perform complex data analysis and investigation for customer requests to explain results and to make appropriate recommendations. - Strong understanding of data modeling concepts. - Problem solver with the initiative to think critically to identify improvement opportunities (error detection, error correction, root cause analysis). - Understand ETL that will aid in verification and testing of data. - Build processes supporting data transformation, data structures, metadata, dependency and workload management. - A successful history of manipulating, processing and extracting value from large disconnected datasets. - Analyze business objectives and develop data solutions to meet customer needs. - Demonstrated ability to effectively participate in multiple, concurrent projects. - Improve and customize current data solutions to meet business functional and non-functional requirements. - Research new and existing data sources in order to contribute to new development, improve data management processes, and make recommendations for data quality initiatives. - Perform periodic data quality reviews for internal and external data. - Ensure timely resolution of queries and data issues. - Look for new ways to find and collect data by researching potential new sources of information. - Work with data and analytics experts to strive for greater functionality in our data systems. Benefits - Medical: Multiple plan options. - Dental: Delta Dental or reimbursement account for flexible coverage. - Vision: Affordable plan with national network. - Pre-Tax Savings: HSA and FSAs for eligible expenses. - Retirement: Competitive retirement package to secure your future. Equal Opportunity All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the "EOE is the Law". Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization.

• Responsible for the data architecture and database design of the Enterprise Data Warehouse, collaborating with other Data platform architects on the overall architecture of the data warehouse ecosystem. • Create logical and physical data models to support analytical needs of the organization, guide and oversee data modeling activities executed at a project or program level • Define data standards, naming conventions, and data architecture best practices. • Ensure data architecture supports all Data Sets (types), and maintains integrity across systems. • Optimize data storage, indexing, and query performance for analytical workloads. • Collaborate with Data Governance team to Implement data policies, including metadata management and data lineage tracking. • Ensure compliance with security, privacy, and regulatory requirements (e.g., GDPR, HIPAA depending on industry). • Work closely with business analysts, data engineers, data scientists, and leadership to translate business needs into technical solutions. • Communicate architectural decisions and provide guidance to development teams. • Collaborate in the evaluation, testing, and recommendation of new tools, platforms, and technologies (cloud data warehouses, BI tools, ETL & MLL frameworks, etc.) • Stay current with trends in data architecture, cloud platforms, and big data technologies. • Monitor data warehouse performance and resolve bottlenecks and/or data quality issues. • Ensure Data design reflects high availability, reliability, and scalability of the data warehouse environment.

Role Description The Data Platform organization is responsible for building the foundational infrastructure, services, and governance that enable the company to operate as a truly data-driven enterprise. Our platform powers analytics, machine learning, experimentation, personalization, business intelligence, and AI initiatives across every function of the company. Today, the organization operates a modern cloud-native data ecosystem spanning data lakes and warehouses, and self-service data capabilities that empower thousands of internal users. As the Senior Director of Data Platform Engineering , you will define and execute the long-term vision for the company's data platform strategy while leading a global organization responsible for the architecture, reliability, scalability, security, and evolution of our enterprise data ecosystem. You will partner closely with Engineering, Product, Data Science, AI/ML, Infrastructure, Security, Finance, and executive leadership to transform data infrastructure into a strategic competitive advantage. This role requires a seasoned technology executive who can balance technical innovation, organizational leadership, operational excellence, and business outcomes while enabling the next generation of AI-powered products and data-driven decision making. As Coursera and Udemy integrate, this role is key to creating a successful data driven company. Responsibilities - Strategic Leadership - Define and execute a multi-year vision and roadmap for the company's enterprise data platform aligned with business and technology strategy. - Drive platform modernization initiatives supporting analytics, AI/ML, experimentation, and product innovation. - Establish engineering investment priorities and technology strategy in partnership with executive leadership. - Organizational Leadership - Build, lead, and scale a high-performing global Data Platform Engineering organization, including senior managers, engineering managers, staff engineers, and principal engineers. - Recruit exceptional technical leaders while developing strong succession planning and leadership pipelines. - Foster a culture of innovation, accountability, operational excellence, and continuous learning. - Platform Architecture & Engineering - Own the architecture and operation of highly scalable cloud-native data platforms supporting petabyte-scale storage and processing. - Lead engineering efforts across batch processing, real-time streaming, metadata management, governance, platform tooling, and self-service infrastructure. - Champion modern engineering practices including Infrastructure as Code, Kubernetes, platform automation, observability, developer productivity, and platform reliability. - Cross-Functional Partnership - Partner with senior leaders across Engineering, Product, AI/ML, Analytics, Infrastructure, Security, and Finance to align platform investments with business priorities. - Serve as the executive sponsor for enterprise-wide data initiatives and influence technical direction across the company. - Represent Data Platform Engineering in executive planning, architecture reviews, and technology governance. - Operational Excellence - Establish KPIs and operational metrics for platform availability, scalability, adoption, reliability, performance, and cloud efficiency. - Drive continuous improvements in developer experience, self-service capabilities, security, compliance, and operational maturity. - Ensure the platform meets enterprise requirements for governance, privacy, and data quality. - Technology Innovation - Evaluate emerging technologies and industry trends to evolve the company's modern data architecture. - Enable AI-first platform capabilities that accelerate machine learning development and data product creation. - Promote technical excellence through architecture reviews, engineering standards, and technical mentorship. Qualifications - 15+ years of experience building and operating large-scale distributed data platforms or cloud infrastructure. - 8+ years of engineering leadership experience managing managers and multi-level engineering organizations. - Demonstrated success building and scaling global engineering organizations supporting mission-critical platforms. - Proven experience defining and executing long-term technology strategies that align with business objectives. - Expertise in Databricks. - Deep expertise in distributed systems, cloud-native architectures, and modern data platforms. - Hands-on knowledge of technologies such as Spark, Kafka, Trino/Presto, Flink, Iceberg, Delta Lake, Airflow, or equivalent large-scale data technologies. - Strong understanding of data warehousing, streaming architectures, lakehouse platforms, metadata management, and data governance. - Expertise with Infrastructure as Code (Terraform, CloudFormation, Ansible), Kubernetes, container orchestration, CI/CD, and cloud-native infrastructure. - Strong understanding of platform observability, reliability engineering, security, and operational excellence. - Outstanding executive communication, organizational leadership, and stakeholder management skills. Preferred Qualifications - Experience implementing enterprise data governance, privacy, compliance, and security programs. - Experience supporting modern lakehouse architectures and data mesh implementations. - Experience leading platform engineering organizations within consumer technology companies. - Experience managing globally distributed engineering organizations across multiple regions. - Demonstrated success influencing executive leadership and board-level technology strategy. - Advanced degree in Computer Science, Engineering, or related field. Benefits - Competitive, zone-based pay aligned to your location, experience, and role level. - Comprehensive health and wellness benefits. - Bonus and RSU equity programs. - Global perks designed to help you grow and thrive wherever you are. Compensation / Location - US Zone 1: $292,000 - $365,000 - US Zone 2: $262,000 - $328,000 - US Zone 3: $248,000 - $310,000 - US Zone 4: $233,000 - $292,000

• Lead the end-to-end delivery of data migration activities across strategic transformation, platform implementation, and legacy system decommissioning programmes. • Define and execute migration strategies, including data profiling, mapping, transformation, mock migrations, dress rehearsals, production cutovers, and post-migration validation. • Analyse complex source and target data models, develop transformation rules, and ensure data quality, integrity, and consistency throughout the migration lifecycle. • Design and perform reconciliation processes across financial, policy, and client data, investigating discrepancies and driving resolution of migration defects. • Collaborate closely with Technology, Operations, Finance, Actuarial, Delivery, and Client stakeholders to ensure successful migration planning and execution. • Identify, manage, and mitigate data migration risks while maintaining governance, auditability, and compliance with regulatory and business requirements. • Drive continuous improvement by enhancing migration processes, automation, tooling, and best practices across programmes.