As the Data Engineer, you will be responsible for expanding and optimizing our data access and data pipeline analytics processes, as well as optimizing data flow and collection for cross functional teams. You will be a data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. You will support our global community of data scientists and analysts on enterprise initiatives and will ensure optimal data delivery is consistent throughout ongoing projects. If you are excited by the prospect of optimizing or even re-designing our company’s analytics processes to support our next generation of advanced analytics capabilities, which in-turn translates to implementing strategic enhancements to maintain our competitive edge in the industry, this may be the opportunity for you.
What skills and background will be important to be successful:
- Minimum 6 years of experience in Business Analytics processes.
- Self-directed and comfortable supporting the data needs of multiple teams, systems and products within the EAP ecosystem.
- Experience with AWS “big data” technologies
- Understanding of distributed systems driving large-scale data processing and analytics with a successful history of manipulating, processing and extracting value from large disconnected datasets
- Familiarity or expertise with technologies like Hadoop (and related ecosystem), Spark, Kafka, EC2, EMR, RDS, and Redshift in supporting data transformation, data structures, metadata, dependency and workload management
- Advanced working database knowledge and experienceworking with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases such as Microsoft and Oracle databases to advance analytics capabilities
- Experience with Data Virtualization is a plus
- Experience with user centered agile methodology is a plus
- BS/BA in Computer Science, Finance or Economics.