Manager, Data Engineering

Medifast, Inc•Headquarters, KY

11d

About The Position

The Manager, Data Engineering is a pivotal leadership role responsible for the architecture, design, and delivery of Medifast’s enterprise data ecosystem. This individual leads a high-performing team to build scalable data pipelines and cloud-based infrastructure (AWS) that power business insights, advanced analytics, and ML/AI initiatives. Acting as a bridge between complex technical architecture and strategic business needs, the Manager ensures that data platforms are reliable, secure, and accessible, while fostering operational excellence and mentoring senior technical talent. Opportunity Highlights · Lead high-impact data engineering and integration initiatives supporting enterprise analytics and business insights · Provide technical and people leadership within a modern, cloud-based data platform environment · Drive architecture, delivery, and operational excellence for scalable, reliable data solutions · Partner with cross-functional stakeholders to translate business needs into production-ready data platforms · Evaluate and introduce new data technologies to improve performance, reliability, and cost efficiency · Champion the 'Simplifying' value by reducing architectural complexity and improving data accessibility across the enterprise.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, or closely related field is required; Master’s degree preferred
5 -7 years in data engineering with demonstrable experience in data integration and data warehouse projects
3+ years of strong programming experience using Python and/or Java.
2+ years’ experience leading data engineering teams using ETL/ELT tools and platforms such as Informatica, AWS Lambda, SSIS, AWS Glue, and/or similar cloud-native integration frameworks
5+ years’ experience with DBMS such as Oracle, SQL Server, MySQL, etc.
3+ years of AWS experience with services such as Amazon Redshift, AWS SQS, etc.
Experience implementing data quality, monitoring, logging, and alerting practices for data pipelines in production environments
Demonstrated ability to communicate complex technical concepts to business and technical stakeholders and translate requirements into scalable solutions
Excellent analytical, problem-solving, and conceptual thinking skills

Nice To Haves

Retail/CPG industry experience preferred

Responsibilities

Translate defined business and analytics requirements into scalable, reliable, and high-performance data engineering and integration solutions.
Provide technical and architectural leadership to ensure data platforms meet established performance, availability, security, and compliance standards.
Provide hands-on technical guidance and support for complex data engineering issues as required.
Accountable for the architecture, design, delivery, and support of systems integration, data warehouse, business insights, and ML/AI use cases.
Partner with cross-functional stakeholders to translate business needs into production-ready data platforms.
Plan and oversee delivery of data engineering initiatives, including effort estimation, prioritization, vendor coordination, and issue escalation.
Ensure data integration services are reliable, secure, scalable, and fit for purpose.
Manage assigned data engineering staff, including work allocation, performance evaluations, coaching, and merit-based compensation recommendations.
Lead agile delivery execution and support continuous improvement of data engineering processes, platforms, and practices.
Foster a culture of technical excellence and professional growth within the data engineering team.
Ensure operational support and stability through established monitoring, logging, alerting, incident management, and 24x7 support processes.
Ensure adherence to change management, release, and deployment standards to minimize operational risk and service disruption.
Identify and implement technology initiatives to improve platform reliability, scalability, and cost efficiency.
Evaluate and introduce new data technologies to improve performance, reliability, and cost efficiency.
Champion the 'Simplifying' value by reducing architectural complexity and improving data accessibility across the enterprise.