Senior Data Engineer

Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. They are seeking a Senior Data Engineer to join their Advanced Data Lake team, responsible for building and operating enterprise data Lakehouse platforms to support large-scale analytics and digital transformation.

Responsibilities:

• We are seeking a talented Senior Data Engineer to join our Advanced Data Lake (ADL) team
• You will build and operate enterprise data Lakehouse platforms that support large-scale analytics and digital transformation
• Your responsibilities will include architecting and maintaining automated data pipelines for ingesting, transforming, and integrating complex datasets
• You will use DataStream for real-time data movement and Dataflow for processing at scale
• Composer/Airflow will be leveraged for seamless scheduling, monitoring, and automation of pipeline operations
• Infrastructure provisioning and workflow management will be handled with Terraform and Dataform to ensure reproducibility and adherence to best practices
• All code and pipeline assets will be managed through git repositories, with CI/CD automation and streamlined releases enabled by Azure DevOps (ADO)
• Changes will be governed by ServiceNow processes to ensure traceability, auditability, and operational compliance
• Core duties involve working with cross-functional teams to translate business needs into pipeline specifications, building and optimizing data models for advanced analytics, and maintaining data quality and security throughout all processes
• You will automate workflow monitoring and proactively resolve data issues, applying strong technical and problem-solving skills
• 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

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