The Lead Data Analytics Engineer will develop and implement the strategies for the data layer for Papa John's analytics stack, top to bottom. He/she will work closely with multiple disciplines from data engineering to data analytics and visualization across all stages of data maturity for the purpose of delivering robust Business Intelligence solutions. This role will research and define software engineering best practices including version control, automated testing, documentation, code review and continuous integration, as essential to any data stack. The Lead Data Analytics Engineer will build data pipelines, craft data visualizations, and assist with a wide range of teams to interpret large quantity of data generated by Papa John's existing systems. He/she will be responsible for everything ranging from collecting data, reporting facts, & investigative analysis. The Lead Data Engineer will also review proposed solutions from data engineers and senior data engineers to ensure long term supportability, best practices, and overall design.
Work with Papa Johns leadership on defining current state and next gen analytics solutions and strategies.
- Lead projects centered on data ingestion, data modeling, and overall data warehouse design.
- Research new technologies and how they can be implemented at Papa Johns.
- Design strategies for enterprise database, data warehouse systems, and multidimensional cubes.
- Set standards for database operations, programming, queries, and security.
- Provide support and guidance to Data Engineers and Senior Data Engineers
- Responsible for the analytics data warehouse, implementing analytical database design principles and establishing business process best practices.
- Develop and support data pipelines, data lake, and data warehouse solution along with finding ways to unlock value from data to support Papa John's business decisions.
- Provide clean data sets / products to product owners, analytics/business intelligence teams and end users.
- Model data to empower and create straight forward data APIs and allow front end developers to easily wire up the visual components.
- Maintain and monitor data pipeline services and BI-platforms.
- Define and leverage engineering methods and best practices to deliver well-defined, tested, documented, and code-reviewed shared data sets.
- Identify, design, and implement internal process improvements (i.e., automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.).
- Cross-functionally supports analytical requests for both internal and external stakeholders.
- Create and maintain optimal data pipeline architecture.
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using ingestion technics and AWS technologies.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing Papa John's product into an innovative industry leader.
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Establish scalable, efficient, automated processes for large scale data analyses, model development, validation, and implementation.
- Solve complex data problems to deliver insights that helps our business to achieve their goals.
- Create data products for analytics and data scientist team members to improve their productivity.
Required
- Bachelor's degree in Computer Science, Information Systems, or related field
- 8+ years experience working as an analytics engineer, data scientist, data engineer, or related
- Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space (GCP experience a plus)
- 8+ years experience hands on development with frameworks such as Python, Java, Scala
- Must have some experience in each of the following skills: Python; Google Big Query, Google Storage, Cloud Composer and Dataflow; Google Pub Sub; SQL; Ansible; Tableau APIs; and Jenkins, and Shell Scripting.
Preferred
Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
Experience in Scala, Python, Pyspark, Java, Rest API, Microservices etc.
Experience in Restaurant or Retail Operations preferred
