Lead Data Engineer; Remote

We are seeking a Lead Data Engineer to provide technical leadership for the Shared Services, Pharmacy, SIU, and Core Functions data portfolios. This role serves as the senior technical leader responsible for partnering with Data Product Managers, architects, business stakeholders, and engineering teams to deliver scalable, reliable, and secure data solutions that support critical enterprise functions including Finance, Human Resources, Legal, Audit, Compliance, Corporate Services, and other shared service domains.

This Lead Data Engineer will drive the modernization and evolution of Care First's data ecosystem, helping establish reusable data products, cloud-native engineering patterns, automated data pipelines, and platform capabilities that improve data accessibility, quality, governance, and operational efficiency. This role combines hands-on technical leadership with solution design, engineering standards, mentoring, and delivery oversight while serving as the primary engineering counterpart to product leadership for strategic EE&EP and Shared Services initiatives.

• Lead the team to design, configure, implement, monitor, and manage all aspects of Data Integration Framework. Defines and develop the Data Integration best practices for the data management environment of optimal performance and reliability.
• Develops and maintains infrastructure systems (e.g., data warehouses, data lakes) including data access APIs. Prepares and manipulates data using Hadoop or equivalent Map Reduce platform.
• Provides detailed guidance and performs work related to Modeling Data Warehouse solutions in the cloud OR on-premise. Understands Dimensional Modeling, De-normalized Data Structures, OLAP, and Data Warehousing concepts.
• Oversees the delivery of engineering data initiatives and projects. Supports long term data initiatives as well as Ad-Hoc analysis and ELT/ETL activities. Creates data collection frameworks for structured and unstructured data. Applies data extraction, transformation and loading techniques in order to connect large data sets from a variety of sources.
• Enforces the implementation of best practices for data auditing, scalability, reliability and application performance. Develop and apply data extraction, transformation and loading techniques in order to connect large data sets from a variety of sources.
• Interprets data, analyzes results using statistical techniques, and provides ongoing reports. Executes quantitative analyses that translate data into actionable insights. Provides analytical and data-driven decision-making support for key projects. Designs, manages, and conducts quality control procedures for data sets using data from multiple systems.
• Improves data delivery engineering job knowledge by attending educational workshops; reviewing professional publications; establishing personal networks; benchmarking state-of-the-art practices; participating in professional societies.

Position does not have direct reports but is expected to assist in guiding and mentoring less experienced staff. May lead a team of matrixed resources.

Education Level: Bachelor's Degree in Computer Science, Information Technology or 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.
Experience: 8 years Experience in leading data engineering and cross functional team to implement scalable and fine-tuned ETL/ELT solutions for optimal performance. Experience developing and updating ETL/ELT scripts. Hands-on experience with application development, relational database layout, development, data modeling.

• Ability to lead the technical design, development, and implementation of complex enterprise data solutions across Shared Services, Employee Experience (EE), and Employee Platform (EP) domains.
• Knowledge of modern data engineering architectures, including cloud-native platforms, data lakehouse patterns, data products, and domain-oriented data ownership.
• Ability to architect and develop scalable ETL/ELT pipelines, data integration services, and enterprise data products supporting operational and analytical workloads.
• Knowledge of cloud data platforms and engineering technologies including Snowflake,Azure Data Services, event-driven architectures, and modern orchestration tooling.
• Ability to establish engineering…