Senior Data Engineer is responsible for designing, implementing and maintaining the enterprise data warehouse, data pipelines and enterprise reporting platform. The individual will support all members of the IT and Business teams on data initiatives and ensure optimal and consistent data delivery processes across all projects. The individual is also responsible for collecting, organizing and analyzing data from multiple platforms to inform the organization and provide actionable business insights.Responsibilities:
- Serve as the subject matter expert for data, analytics, and testing within IT, supporting all other functional areas such as Marketing, Operations, Distribution Center, Finance, Facilities Support to identify the most impactful ways for data and analytics to drive decision making.
- Perform deep-dive analysis including the application of advanced analytical techniques to solve some of the more critical and complex business problems such as customer segmentation and targeting, and supply chain optimization.
- Create new methods to visualize core business metrics through reports, dashboards, and analysis in Power BI and SSRS to surface trends.
- Design and build solutions to empower stakeholders across Cumberland Farms to self-serve analytics needs.
- Develop standards for best practices for reporting, marketing, and educating the company on available reporting tools in the company
- Design, Implement and Maintain the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and ‘big data’ technologies into a Data Warehouse based on internal process improvements, automation and optimization of data delivery.
- Assemble large, complex data sets that meet functional / non-functional business requirements and design custom ETL and ELT processes in support of these processes
Computer Science, Engineering, Mathematics or a related technical discipline.Preferred Education:
Advanced quantitative technical degree (MS or PhD) preferredMinimum Experience:
At least 10 years of professional experience in data analysis including SQL, database modeling and design.
- Excellent communication skills, particularly translating between technical and non-technical stakeholders
- Advanced knowledge with SQL, DAX, M and Python.
- Deep understanding of data integration and transformation patterns such as messaging, ETL
- Machine learning knowledge/experience.
- Experience working with both SQL and NoSQL databases and their query authoring (SQL) languages
- Experience with Analysis Services, MS SQL Server Reporting Services (SSRS), Power BI, and other visualization tools.
- Strong visual design skills used to create reports and dashboards
- Background in Data Science with an understanding of the principles of machine learning.
- Strong project management and organizational skills.