Callaway Golf Company is a leader in total performance, premium golf equipment and active lifestyle products while also being a great place to work! We are passionate and push the limits of innovation. We dare to be great while acting with integrity and respect. We stay hungry, yet humble. All while having fun and making golf enjoyable for everyone!
Our company is a blend of experience and diverse backgrounds, and our leaders have a strong history of building and selling successful initiatives. We are working to build a truly groundbreaking company, and we want top-notch people to join us in that mission.
We are looking for a skilled Data Engineer to join our Research and Development Team implementing data pipelines for use in our Data Science based product design. The hire will be responsible for the data and data pipeline architecture, as well as the CI/CD of the data to the R&D department and collaborating departments. The ideal candidate will be comfortable taking the lead in the data organization, pipelining, and wrangling of the data. The Data Engineer will support our data scientists, product designers, product analysts, and business analysts on data initiatives and will ensure optimal data delivery architecture is consistent throughout the ongoing projects. This ideal candidate will enjoy training business analysts in the company on the best practices in accessing the data. The right candidate will enjoy learning and keeping up to date on modern data architecture and technologies to optimize the delivery, efficiency, and accuracy of the data. The ideal candidate has a track record of successfully delivering self service data.
ROLES AND RESPONSIBILITIES
- Build DataOps for a modern approach to data
- Create and maintain data pipeline architecture in a CI/CD framework built for self service data.
- Assemble large, complex data sets that meet the data customers&rsquo needs and enrich the data sources where possible.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing existing processes for better data flow and accuracy.
- Build the infrastructure required for optimal data flow in Azure cloud technologies using a mix of open source and licensed technologies.
- Document data schema and architecture design decisions for handoff to other teams and data scientist.
- Keep data separated and secure across national boundaries through multiple regions and data centers.
- Monitor data pipelines to preempt data delivery issues.
- Manage Data initiative projects from start to finish
- Research and test new tools and technologies
TECHNICAL COMPETENCIES Knowledge, Skills & Abilities
- Experience with Big Data Tools: Databricks or equivalent
- Experience with SQL and NoSQL Databases: MSSQL, Azure SQL, Azure Synapse and Azure Cosmos DB or equivalents
- Experience with data pipeline and workflow management tools: Azure Data Factory, Airflow, or equivalents
- Experience with stream-processing systems: Azure Event Hub, Kafka, or equivalents
- Experience with IaC and CI/CD integration.
- Ability to work well with all levels of the organization in fast paced, dynamic environment. Cultivates positive relationships with other associates and collaborate with others in cross-functional teams.
- Ability to interface with other groups and disciplines to successfully complete assignments and to make recommendations. Ability to work beyond functional boundaries to identify opportunities, develop and implement solutions to improve company performance.
- Able to consistently make data-driven decisions.
EDUCATION AND EXPERIENCE
- We are looking for a candidate with 3+ years experience in a Data Engineering role, who has attained a Graduate Degree in Computer Science, Information Systems, Engineering, or other quantitative field. Cloud based certifications a plus.
- Track record of organizing dispersed datasets across different teams of people.
- Focus on self-growth and improvement for the betterment of the business objectives.
Callaway Golf is an Equal Opportunity Employer.