Manager of Data Engineering

The Enterprise Data Analytics (EDA) division at Renown Health oversees the analytics lifecycle to identify, analyze and present relevant insights that drive administrative, clinical, and financial decisions and anticipate opportunities to achieve a competitive advantage.

The Manager of Data Engineering oversees planning, development, implementation, and ongoing support for Analytic tools, including the Enterprise Data Warehouse (EDW) within Microsoft Azure's Cloud, third party business intelligence tools such as Business Objects, and ETL pipelines to distribute data internally and externally. Leads the EDW Steering committee to establish the strategic direction and to set priorities for the implementation and use of the EDW and analytics. Collaborates with EDA data analysts and data scientists in the development and implementation of data governance standards. Assists staff with career development planning to build and grow the depth of data engineering and analytics knowledge.

This is an important role where you will work on our entire data architecture, developing strategies to ensure data quality, optimize data transformation, and standardize data modeling. Additionally, as the data engineering manager you will work closely with our data science, data engineering, and analytics teams to identify areas for improvement and develop innovative solutions to complex data problems in healthcare.

This role is designed as hybrid.

Primary Responsibilities:

* Take a leading role in the Division's development of Enterprise Data strategy, architecture, policies, and governance structure and will support the organization in taking a strategic approach to choosing the right processes, technologies and resources to be implemented and embedded within our rapidly growing organization.

* Play a pivotal role in shaping our future data architecture and capability by facilitating the creation of processes, policies, and standards as well as shaping and laying foundations for the underpinning technologies.

* Be one of the key contributors to the organizations digital transformation initiatives aimed at driving a deep organizational change to transition from the current local and fragmented state to a unified data source operating model.

* Seek to develop a unified, single source of truth for the organizations data and analytics customers as well as provide recommendations for tools and technology to modernize data systems, applications, ETL processes and other capabilities.

* Assemble teams that perform modernized ETL processes on large, complex sets of data that meet non-functional and functional business requirements.

* Identify, design, and implement internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes.

* Outline and implement a modern data stack as an integrated set of tools that helps facilitate the handling, cleaning, processing, and storing of data for the organization.

* Design end-user engagement layers that support the needs of the data science quality, and other analytics teams.

* Keep abreast of technological advances in cloud data structures including Data warehouses, Data Streams, Data lakes, Pipelines for ingesting and processing data, and Catalogs for data organization.

* Lead BI & Analytics teams to define Information and MDM Solution Architecture.

* Implement system improvements and new technologies aimed at data storage, profiling, processing, management and streamlining external data source ingestion.

* Recommend improvements and platform development to meet strategic objectives of the business (e.g., workflow mgmt. applications, data cleansing, auditing, monitoring, etc.).

* Review gap analysis of current business systems, EDW, Data Stores, and tabular data structures and applications to target state.

* Create functional specifications and testing requirements for system and configuration changes due to application modifications.

* Understand existing business applications and legacy systems landscape to support information and solution architecture.

* Support the organization in establishing a standard for ETL pipeline processes in coding, architecture, and design of the data warehouse and data lake.

* Build required infrastructure for optimal extraction, transformation and loading of data from various data sources using Azure, Python, and SQL technologies.

* Facilitate the establishment of change management processes to prepare, monitor, and maintain the systems that will provide production ready data.

* Develop and own process for evaluating and auditing ETL loads and extracts including failures/success rates (establish relevant KPIs, etc.) and providing direction to the team for improvement.

* Set up and review data standards, classifications, mappings, cross-referencing and metadata to support both EDW and Data Lake architecture.

* Define the desired data warehouse solution feature set.

* Provide management and mentoring to subordinate Team Members.

* Provide team leadership, management, development and coaching as required.

Incumbent Must Possess:

* Extensive knowledge in SQL and relational databases.

* Five plus (5+) years of healthcare domain preferred.

* Demonstrated strong domain knowledge with expertise in payer/provider health data engineering and business functions specifically in areas of administrative and clinical operations.

* Engineering or analytic team management/lead experience.

* Demonstrated ability in the application of Lean thinking, continuous improvement, and change management.

* Ability to support the development of engineers for EDW development and programming skills (e.g., SQL, Python, Alteryx).

* Experience working with IT partners or automation strategies to deploy production-level analytic solutions.

This position does not provide patient care.

The foregoing description is not intended and should not be construed to be an exhaustive list of all responsibilities, skills and efforts or work conditions associated with the job. It is intended to be an accurate reflection of the general nature and level of the job.

Name

Description

Education:

Must have working-level knowledge of the English language, including reading, writing, and speaking English. Master's degree in computer science, software engineering, data science, or related discipline preferred. Educational requirement can be waved with over 10 years of data engineering or data analytics experience and 5 years' experience in healthcare.

Experience:

Strong engineering background with 10+ years of professional working experience, of which at least 5+ years of experience in a Data Engineering, Data Science, or Analytics Engineering capacity.

License(s):

None

Certification(s):

Ability to obtain one of the following certificates within 12 months of hire.

* Epic Cogito

* Epic Cosmos Data Model for Data Architects

* Alteryx Designer Core

* Microsoft Azure Data Engineer Associate

Must stay current on new version certification as applicable.

Computer / Typing:

Must be proficient in Microsoft Office Suite, including Outlook, PowerPoint, Excel, Teams and Word and have the ability to use the computer for online learning requirements for job-specific competencies, access online forms and policies, complete online benefits enrollment, etc.