Data Engineer II

About the Opportunity

At Medifast, our team members are relentless in our mission of driving Lifelong Transformation, Making a Healthy Lifestyle Second Nature™. When you join Medifast, you become part of a dynamic, fast-growing community of highly motivated, like-hearted people who share a passion for promoting health and wellness. Just as OPTAVIA Coaches inspire Clients to reach their personal wellness goals, at Medifast, we inspire each other to bring our best to work each day to further our shared mission. If you want to build a rewarding career that makes lives better on a daily basis, Medifast may be the perfect place for you.

Overview of Position

Data Integration Engineer will work closely with cross functional team of product managers, solution architects, engineers, and integrators to enable data org; while key responsibilities include directing code design and delivery tasks associated with the integration, cleaning, transformation, and control of data in operational and analytical data systems; working with the Project Management team to define outcomes and inform work structures. The Data Engineer role will be responsible for developing and implement a range of analytics and automation solutions, including data extraction, analysis, reporting, and dashboard design, but could include more advanced analytics including statistical analysis, text mining & NLP, and modeling/machine learning/AI, as required

II. Job Responsibilities

Analysis & Planning:

• Analyze various data sources, defining & validating data objects and identifying the relationship among them.

• Assembles large, complex data sets that meet functional and non-functional requirements, ensuring that the design and engineering approach is consistent across multiple systems

• Leads the identification of gaps in data management standards adherence and works with appropriate partners to develop plans to close gaps, leading concept testing and conducting research to prototype toolsets and improve existing processes

Design & Documentation

• Utilizes appropriate architectural components in the design and development of client requirements and collaborates with development teams to understand data requirements and ensure the data architecture is feasible to implement
• Proficient with design and ticketing tools like Lucid Chart, Visio, Power Point, Jira, Confluence etc.

Tools & Platforms

• Defines and builds data pipelines to enable data-informed decision making, ensuring adherence to release processes and risk management routines.

• Maintains, improves, cleans, and manipulates large data for operational and analytics data systems, builds complex processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management, and communicates required information for deployment, maintenance, and support of business functionality

• Experience and knowledge of data governance with data catalogs, data quality and data accessibility are much desirable

• Responsible for multiple projects simultaneously, ensuring each one is completed on time and efficiently with a high standard for quality. Collaborate with agile team in the planning, design and development, of new Integrations, to support data analytics and data science team.

• Self-driven and responsible for successful delivery of project from initiation to execution.

Leadership

• Mentors offshore team of data engineers in the delivery and release of continuous integration and continuous delivery events and defines key performance indicators and internal controls

• Coordinates, schedules, participate in cross-functional analytics & automation activities

III. Scope

Data engineering needs across business functions. Managing geographically dispersed internal/external team members across remote locations and Baltimore (HQ), and Utah.

IV. Knowledge, Education, Skills & Abilities

• Bachelor’s degree in Computer Science, Information Systems, or Engineering.
• Proficient using AWS Services for data integrations and governance like – building data lakes with Amazon S3 and Glue, data integration using AWS Lambda, Event bridge, Kinesis streams etc., using data analytics services like Athena, Redshift, EMR or on other cloud platform services
• 4+ years in a data engineering role with demonstrable experience in data integration and data warehouse projects using some of the leading ETL Tools like Databrick