Senior Data Engineer

Mayo Clinic is a top-ranked healthcare provider dedicated to putting patient needs first while investing in employee success. They are seeking a Senior Data Engineer to join their Advanced Data Lake team, focusing on building and operating data platforms to support analytics and digital transformation initiatives.

Responsibilities:

• Build and operate enterprise data Lakehouse platforms that support large-scale analytics and digital transformation
• Architect and maintain automated data pipelines for ingesting, transforming, and integrating complex datasets
• Use DataStream for real-time data movement and Dataflow for processing at scale
• Leverage Composer/Airflow for seamless scheduling, monitoring, and automation of pipeline operations
• Handle infrastructure provisioning and workflow management with Terraform and Dataform to ensure reproducibility and adherence to best practices
• Manage all code and pipeline assets through git repositories, with CI/CD automation and streamlined releases enabled by Azure DevOps (ADO)
• Govern changes by ServiceNow processes to ensure traceability, auditability, and operational compliance
• Work with cross-functional teams to translate business needs into pipeline specifications
• Build and optimize data models for advanced analytics
• Maintain data quality and security throughout all processes
• Automate workflow monitoring and proactively resolve data issues

Requirements:

• 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
• Ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes
• Interpersonal skills, time management skills, and demonstrated experience working on cross functional teams
• Strong analytical skills and the ability to identify and recommend solutions and a commitment to customer service
• Excellent verbal and written communication skills, attention to detail, and a high capacity for learning and problem resolution
• Advanced experience in SQL
• Strong Experience in scripting languages such as Python, JavaScript, PHP, C++ or Java & API integration
• Experience in hybrid data processing methods (batch and streaming) such as Apache Spark, Hive, Pig, Kafka
• Experience with big data, statistics, and machine learning
• Ability to navigate linux and windows operating systems
• A GCP Professional Data Engineer certification is required
• Knowledge of workflow scheduling (Apache Airflow Google Composer)
• Infrastructure as code (Kubernetes, Docker)
• CI/CD (Jenkins, Github Actions)
• Experience in DataOps/DevOps and agile methodologies
• Experience with hybrid data virtualization such as Denodo
• Working knowledge of Tableau, Power BI, SAS, ThoughtSpot, DASH, d3, React, Snowflake, SSIS, and Google Big Query
• Google Cloud Platform (GCP) certification
• Hybrid or multi-cloud experience
• Familiarity with enterprise data governance, metadata, and lineage tools
• Experience working in large, regulated environments