OVERVIEW Responsible for developing complex, large scale data models and pipelines that organize and standardize the data to make it readily accessible and consumable by the business for reporting and data science needs. Collaborate with various areas of the Business in order to determine and source the appropriate data through internal and external means. Investigate new and existing technologies and data sources and assess their viability within the Sheetz environment. RESPONSIBILITIES (other duties may be assigned) 1. Co-lead in the selection and build of our data and analytic tools including Enterprise Data Warehouse, Data Lake, Analytics platform and Data Catalogue. 2. Design, implement, manage data architecture and data pipeline across multiple data sources. 3. Collaborate closely with Business and Technical Owners in identifying data sources and aggregating structured or unstructured data into dimensional data models able to be consumed by the business. 4. Identify potential process improvements and designs and implement automated solutions. 5. Manage the democratization of data knowledge across the organization through the communication and maintenance of master data, metadata, data management repositories, data models, and data standards 6. Establish standardization and educate data users on query best practices allowing for re-use and analytic efficiency. QUALIFICATIONS (Equivalent combinations of education, licenses, certifications and/or experience may be considered. Two years of experience is equivalent to one year of college/trade school) Education • Bachelor degree in Computer Science, Management Information Systems, Computer Engineering or a related field required. • Master’s degree in Computer Science, MIS or Computer Engineering preferred. Experience • Minimum 5 years working in a Data Engineer role required • Minimum 5 years working with large databases and data warehouses utilizing both relational and non-relational data models required • End to end experience in the analytic lifecycle from structured/unstructured raw data, data wrangling, creating data pipelines, to self-service dashboards leveraged by the business required • Advanced knowledge of SQL required • Minimum 5 years development experience in at least one object-oriented language (Python, Perl, Java, etc.) required • Proficiency in data visualization tool (Tableau) preferred • Strong understanding of cloud computing database technologies (Azure, AWS, GCP) required • Experience building and optimizing “Big Data” pipelines, architectures and data sets required • Experienced with data wrangling and preparation for use within data science, business intelligence or similar analytical functions required Licenses/Certifications • None Required Tools & Equipment • General Office Equipment(Equivalent combinations of education, licenses, certifications and/or experience may be considered. Two years of experience is equivalent to one year of college/trade school) Education • Bachelor degree in Computer Science, Management Information Systems, Computer Engineering or a related field required. • Master’s degree in Computer Science, MIS or Computer Engineering preferred. Experience • Minimum 5 years working in a Data Engineer role required • Minimum 5 years working with large databases and data warehouses utilizing both relational and non-relational data models required • End to end experience in the analytic lifecycle from structured/unstructured raw data, data wrangling, creating data pipelines, to self-service dashboards leveraged by the business required • Advanced knowledge of SQL required • Minimum 5 years development experience in at least one object-oriented language (Python, Perl, Java, etc.) required • Proficiency in data visualization tool (Tableau) preferred • Strong understanding of cloud computing database technologies (Azure, AWS, GCP) required • Experience building and optimizing “Big Data” pipelines, architectures and data sets required • Experienced with data wrangling and preparation for use within data science, business intelligence or similar analytical functions required Licenses/Certifications • None Required Tools & Equipment • General Office Equipment1. Co-lead in the selection and build of our data and analytic tools including Enterprise Data Warehouse, Data Lake, Analytics platform and Data Catalogue. 2. Design, implement, manage data architecture and data pipeline across multiple data sources. 3. Collaborate closely with Business and Technical Owners in identifying data sources and aggregating structured or unstructured data into dimensional data models able to be consumed by the business. 4. Identify potential process improvements and designs and implement automated solutions. 5. Manage the democratization of data knowledge across the organization through the communication and maintenance of master data, metadata, data management repositories, data models, and data standards 6. Establish standardization and educate data users on query best practices allowing for re-use and analytic efficiency.