Data Engineering Manager (Remote)

CareFirst•Baltimore, MD

1d•Remote

About The Position

We are seeking a Manager, Data Engineering to lead a team responsible for delivering and supporting critical data platforms and solutions that enable CareFirst's HEDIS, Stars, Quality Measurement, and Risk Adjustment programs. This role will partner closely with business and technology stakeholders to ensure trusted, scalable, and timely data capabilities that support quality improvement initiatives, regulatory reporting, member outcome measurement, and accurate risk capture across the enterprise. In addition to people leadership responsibilities, the Manager, Data Engineering will provide technical leadership for the design, development, and operation of modern data engineering solutions, including data pipelines, integrations, cloud-based platforms, data transformation processes, and enterprise data products. This role will be responsible for ensuring the reliability, scalability, security, and performance of critical healthcare data assets while driving modernization efforts, engineering best practices, platform stability, automation, and operational excellence across a complex data ecosystem.

Requirements

Bachelor's Degree in Computer Science, Information Technology, Engineering, or related field OR in lieu of a Bachelor's degree, an additional 4 years of relevant work experience is required in addition to the required work experience.
5 years Related professional experience.
1 year Supervisory or demonstrated progressive leadership experience.
Ability to lead and develop high-performing data engineering teams while aligning technology strategy to business objectives and regulatory requirements.
Knowledge of modern data engineering architectures, including cloud-native platforms, data lakes, lakehouses, real-time processing, and enterprise data products. (Azure, Snowflake, IDMC, Fabric).
Knowledge of healthcare data domains, including claims, enrollment, provider, clinical, and quality measurement data used in HEDIS, Stars, and Risk Adjustment programs, including experience with HEDIS engines.
Knowledge of CMS regulatory reporting and data submission processes, including Risk Adjustment, EDGE Server submissions, RADV audits, and related healthcare regulatory requirements.
Ability to design, implement, and support scalable data pipelines, ingestion frameworks, and data integration solutions supporting enterprise analytics and operational workloads.
Knowledge of Agile delivery methodologies, DevOps practices, CI/CD pipelines, and infrastructure automation principles.
Knowledge of enterprise data governance, metadata management, lineage, and data quality control practices.
Proficient in programming and scripting languages used for data engineering, including Python, SQL, and other automation technologies.
Skill in communication, including executive presentations, stakeholder updates, and technical documentation.
Knowledge of budget planning, resource management, vendor oversight, and technology investment prioritization.
Ability to evaluate emerging technologies and establish technical roadmaps that support long-term scalability, data democratization, and analytics maturity objectives.
Must be able to meet established deadlines and handle multiple customer service demands from internal and external customers, within set expectations for service excellence.
Must be able to effectively communicate and provide positive customer service to every internal and external customer, including customers who may be demanding or otherwise challenging.
Must be eligible to work in the U.S. without Sponsorship

Responsibilities

Manage the design of robust, reusable and scalable data driven solutions and data pipeline frameworks to automate the ingestion, processing, and delivery of structured and unstructured batch and real-time streaming data.
Drives technical delivery and works with team on strategy and execution.
Oversees the development of data delivery services to support critical operational processes, analytical models, and machine learning applications.
Understand and implement best practices in management of enterprise data, including master data, reference data, metadata, data quality, and lineage.
Develops a data culture and finds innovative approaches to train the data team.
Work collaboratively with other technology teams, data scientists, analytics teams, and business product owners in an agile environment.
Manage the selection and integration of data related tools, frameworks, and applications required to expand our platform capabilities.
Manages the maintenance of automated processes with a special focus on data flow and error recovery.
Provides support during technical project life cycle and ensures targets are achieved in a timely manner.
Stays up to date on data industry innovations and trends.