Manager, Data Engineering

📋 Description

• • Lead and manage the strategic direction and operational execution of Centene Corporation's data platform and infrastructure, ensuring its scalability, reliability, and efficiency to support the health outcomes of over 28 million members.
• • Mentor and guide a high-performing team of data engineers, fostering a collaborative and inclusive environment that encourages professional growth and innovation.
• • Drive the development and implementation of robust processes and technologies for large-scale data pipelines, optimizing data availability and accessibility for generating critical business insights.
• • Translate complex business objectives and technical requirements into actionable designs, leveraging best-practice design patterns and collaborating closely with engineering leads, product managers, and design leads to shape the future technical roadmap for data engineering.
• • Oversee the end-to-end lifecycle of data production projects, from planning and prioritization through execution, ensuring timely and high-quality delivery of data products.
• • Champion the development of software code for formatting, tagging, processing, storing, and delivering data, ensuring accuracy and consistency across all data assets.
• • Establish and enforce rigorous standards and processes for data quality, integrity, and governance, ensuring that all data products meet the highest levels of accuracy and trustworthiness.
• • Lead code reviews, facilitate technical discussions, and maintain accountability for the agile processes and ceremonies within the data engineering team, promoting efficient workflows and continuous improvement.
• • Manage and direct the automation of key ETL/ELT processes and quality assurance measures, working in conjunction with the quality engineering team to handle large volumes of data and facilitate seamless workload migrations.
• • Play a pivotal role in data governance initiatives, including data quality monitoring, integrity checks, adherence to standards, master data management, metadata strategy development, and supporting business intelligence and analytics functions.
• • Contribute significantly to critical technology decisions for data pipelines, ensuring that chosen solutions are scalable, repeatable, secure, and capable of serving the organization's extensive user base.
• • Effectively allocate available resources to meet operational objectives, demonstrating strong leadership and a commitment to fostering a diverse and inclusive workplace culture.
• • Ensure compliance with all company policies, standards, and regulatory requirements, maintaining the highest ethical and professional conduct.
• • Drive innovation in data engineering practices, exploring and implementing new technologies and methodologies to enhance data processing capabilities and unlock new analytical opportunities.
• • Collaborate with cross-functional teams, including analytics, business intelligence, and application development, to understand their data needs and deliver solutions that drive business value.
• • Develop and maintain comprehensive documentation for data pipelines, processes, and architecture, ensuring knowledge transfer and maintainability.
• • Proactively identify and address potential data-related risks and challenges, implementing mitigation strategies to ensure data integrity and security.
• • Contribute to the strategic planning of the data technology roadmap, aligning data engineering efforts with broader business goals and digital transformation initiatives.
• • Empower team members through coaching, training, and performance management, cultivating a culture of continuous learning and skill development.
• • Act as a key stakeholder in vendor selection and management for data-related tools and services, ensuring alignment with technical requirements and budget constraints.
• • Champion data literacy across the organization, promoting understanding and effective utilization of data assets by various business units.
• • Ensure the data platform is resilient and capable of handling peak loads and unexpected events, implementing robust monitoring and alerting systems.
• • Drive the adoption of data quality frameworks and best practices, embedding quality checks throughout the data lifecycle.
• • Contribute to the development of a comprehensive data catalog and metadata management system, enhancing data discoverability and usability.
• • Oversee the implementation and maintenance of data security protocols and access controls, safeguarding sensitive member information.
• • Foster a culture of continuous improvement within the data engineering team, encouraging the adoption of new tools, techniques, and methodologies.
• • Act as a subject matter expert on data engineering principles, best practices, and emerging trends, providing guidance and thought leadership to the organization.