Manager, Data Engineering (Hybrid Work Schedule)

Date: Jan 19, 2023

Location: Rancho Cucamonga, CA, US

Company: Inland Empire Health Plans

Job Requisition ID: 8523 

 

Position Summary/Position

 

The Manager, Data Engineering is responsible for architecting, building, maintaining, and improving data infrastructure. This role will work closely with data scientists, data analysts, and the business intelligence teams to ensure a unified data architecture model that supports the company’s strategic and functional needs. The Manager, Data Engineering will monitor cross-functional work that overlaps with other data functions across the organization by ensuring business areas that use and ingest data are channeled through the enterprise data warehouse and data assets. This is a hands-on management position that is responsible for assembling teams that perform modernized Data Engineering and ETL processes on large, complex sets of data that address functional, non-functional, explicit, and implicit business requirements.  This role is also responsible for identifying, designing and implementing internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes.  

Major Functions (Duties and Responsibilities)

 

1. 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.
2. 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. 
3. 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.
4. 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.
5. Assemble teams that perform modernized ETL processes on large, complex sets of data that meet non-functional and functional business requirements.
6. Identify, design and implement internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes.  
Platform
7. 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.
8. Design end-user engagement layers that support the needs of the data science quality, and other analytics teams. 
9. 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. 
10. Lead BI & Analytics teams to define Information and MDM Solution Architecture.
11. Implement system improvements and new technologies aimed at data storage, profiling, processing, management and streamlining external data source ingestion.
12. Recommend improvements and platform development to meet strategic objectives of the business (e.g., workflow mgmt. applications, data cleansing, auditing, monitoring, etc.).
13. Review gap analysis of current business systems, EDW, Data Stores, and tabular data structures and applications to target state.
14. Create functional specifications and testing requirements for system and configuration changes due to application modifications.
15. Understand existing business applications and legacy systems landscape to support information and solution architecture.

Major Functions (Duties and Responsibilities) Cont

 

Process
16. Support the organization in establishing a standard for ETL pipeline processes in coding, architecture, and design of the data warehouse and data lake.
17. Build required infrastructure for optimal extraction, transformation and loading of data from various data sources using Azure, Python, Hbase, Hadoop, and SQL technologies.
18. Build analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition.
19. Facilitate the establishment of change management processes to prepare, monitor, and maintain the systems that will provide production ready data. 
20. Develop and own process for evaluating and auditing ETL loads including failures/success rates (establish relevant KPIs, etc.) and providing direction to the team for improvement.
21. Set up and review data standards, classifications, mappings, cross-referencing and metadata to support both EDW and Data Lake architecture.
22. Define the desired data warehouse solution feature set.
23. Choose the optimal deployment option (on-premises/in-cloud/hybrid).
24. Choose the optimal architectural design approach to building a data warehouse.
25. Select the data warehouse technologies (EDW database, ODS, Data Lake, and data streaming, ETL/ELT tools, data modeling tools, etc.), considering number of data sources and data volume to be loaded into the data warehouse, data flows to be implemented, and data security requirements.
26. Maintain a solid understanding emerging technologies in digital transformation to support continuous improvement for all data mechanisms. 
People
27. Work with stakeholders including data, design, product, and executive teams and assisting them with data-related technical issues.
28. Work with stakeholders including the Executive, Product, Data and Design teams to support their data infrastructure needs while assisting with data-related technical issues.
29. Provide management and mentoring to subordinate Team Members.
30. Provider team leadership, management, development and coaching as required.

Supervisory Responsibilities

Leader: Administers Hires, Terminations, and Performance Reviews

Experience Qualifications

 

Minimum ten (10) years of relevant experience:
- In Data management and governance.
- In Data engineering.
- With developing data mappings, data extractions, data transformations that support the organization’s data warehouse environment.
- In planning, designing, and overseeing the technical transitions between development, testing, and production phases of data warehouse deployment. 
- With facilitating change control and problem management among data warehouse development and support teams.
- In data normalization using standard models like OMOP.
- Healthcare data interoperability, parsing experience using HL7 tools and protocols like FHIR and V2, V3 and persist data in RDBMS.
- Healthcare data background handling PHI and de-identified data.
- In overseeing and directing platform offerings related to big data compute, cloud storage, and job deployment. 
- With leading a team that ensures these platform offerings scale with our growing business; this includes aligning our offerings with the broader application landscape, innovating on newer initiatives around metadata management, data products, and simplifying data access rules.
- In job scheduling with products like Airflow or data warehousing with Redshift/Snowflake.
- In transformation, preparation, and aggregation of HL7 data to present to business stakeholders.
- In creating SOAP/REST based API integrations to ingest and share EHR data.
- In-depth knowledge and experience with data validation on clinical resources (Lab results, Condition, Procedures, immunization, encounter etc.).
- Experience with HL7 processing and programming on the Azure public health cloud API platform, importing file resource segments into Azure’s relational model, for visualization in Tableau or other dash boarding platform.

Preferred Experience

 

Data Management and governance experience preferably setting up, leading or transforming a Data Engineering teams in complex business environments. Five plus (5+) years of healthcare domain preferred.
 

Education Qualifications

 

Bachelor’s Degree in Computer Science, Software Engineering or similar Analytical discipline from accredited institution required.

Preferred Education

 

Master’s degree from an accredited institution preferred.

Drivers License Required

No

Knowledge Requirement

 

- Knowledge of BI & Analytics, industry trends and how they interrelate to the organizational needs. 
- Extensive background in database systems along with a strong knowledge of SQL, Python, Scala, or other industry languages.
- Microsoft Azure Data Platform services including Azure Data Lake Store, Azure Storage, Azure Synapse, Azure Data Factory, Azure SQL database, Logic Apps, APIs.
- Familiar with healthcare data integration specifications (e.g. HL7 2.x, C-CDA, and FHIR).
- Solid understanding of HL7 V2 and V3 data structures.
- Strong understanding of database structures, theories, principles, and practices.
- Knowledge of applicable data privacy practices and laws.
- Knowledge of applicable data privacy practices and laws. Familiar with metadata management, data lineage, and the fundamental principles of data governance (such as data quality, access requests and controls).

Skills Requirement

 

Excellent project management skills. Demonstrated oral and written communication skills. Extensive database management experience with excellent database skills. Proven analytical and problem-solving skills.

Abilities Requirement

 

Demonstrated ability to manage multiple and complex projects. Ability to spot and correct problems before they surface. Ability to determine long term directions. Must be creative, flexible, proactive, and able to work in a fast paced and ever-changing environment, organize and prioritize work, meet deadlines, and work independently.

Commitment to Team Culture

 

The IEHP Team environment requires a Team Member to participate in the IEHP Team Culture. A Team Member demonstrates support of the Culture by developing professional and effective working relationships that include elements of respect and cooperation with Team Members, Members and associates outside of our organization.

Work Model Location

Hybrid

Physical Requirements

Hearing: One-on-One - FREQUENTLY
Communicate: Information/ideas verbally - FREQUENTLY
Near Visual Acuity - FREQUENTLY
Regular contacts: co-workers, supervisor - FREQUENTLY
Memory - FREQUENTLY
Understand and follow direction - FREQUENTLY
Regular and reliable attendance - CONSTANTLY
Keyboarding: 10-Key - FREQUENTLY
Keyboarding: Touch-Screen - FREQUENTLY
Keyboarding: Traditional - FREQUENTLY
Sitting - CONSTANTLY
Indoors - FREQUENTLY
Lighting - CONSTANTLY

A reasonable salary expectation is between $134,804.80 and $171,870.40, based upon experience and internal equity.

Inland Empire Health Plan (IEHP) is the largest not-for-profit Medi-Cal and Medicare health plan in the Inland Empire. We are also one of the largest employers in the region, designated as “Great Place to Work.” With a provider network of more than 5,000 and a team of more than 3,000 employees, IEHP provides quality, accessible healthcare services to more than 1.5 million members. And our Mission, Vision, and Values help guide us in the development of innovative programs and the creation of an award-winning workplace. As the healthcare landscape is transformed, we’re ready to make a difference today and in the years to come. Join our Team and make a difference with us! IEHP offers a competitive salary and stellar benefit package with a value estimated at 35% of the annual salary, including medical, dental, vision, team bonus, and state pension plan.


Nearest Major Market: Riverside
Nearest Secondary Market: Los Angeles