Data Engineering Manager (Remote)

CareFirst•Baltimore, MD

1d•Remote

About The Position

We are seeking a Manager of Data Engineering to lead and strengthen our data engineering capabilities within the organization. This role is responsible for driving execution excellence, delivering scalable data solutions, and supporting the evolution of our data platforms. As a hands-on leader, you will oversee a team of data engineers responsible for building and maintaining modern data pipelines and platforms. You will work closely with architecture, governance, analytics, product, and business stakeholders to deliver high-quality, reliable, and secure data products that enable data-driven decision-making across the enterprise. The ideal candidate combines strong technical expertise with people leadership skills, operational discipline, and a collaborative mindset.

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.
Strong background in building and supporting scalable data pipelines (real-time streaming, batch processing), data APIs, and integrations.
Thorough understanding of data structures, data modeling, and schema design.
Strong experience in Snowflake, Azure Data Factory, Informatica IICS and Azure Dev Ops/CI-CD.
Proficient in programming languages (e.g., SQL, Python, R, Ruby, Java).
Skilled in leading iterative development cycles with measurable outcomes.
Ability to adapt and respond quickly to shifting priorities, ensuring minimal disruption and maximum ROI.
Capable of guiding teams through complex challenges, while empowering them to innovate and grow.
Strong knowledge of Healthcare payer domain specifically around Cost of Care and Value Based program reporting.
Skilled in communicating to others to convey information effectively.
Ability to create and present presentations.
Skill in communication via the written word.
Ability to interpret and relate the business strategy and vision to the data team.
Ability to maintain effective interpersonal relationships.
Knowledge of budget control methods, policies, and procedures.
Ability to work in an Agile environment and collaborate effectively with product owners, product managers, scrum masters and other technical and non-technical stakeholders.
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.

Nice To Haves

Data Management\Certified Analytics Professional (CAP) Preferred Upon Hire

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.