The Data Engineers are responsible for applying a breadth of knowledge, deep technical skills, and strategic thinking to build custom data pipelines and business intelligence/analytic systems across our technology stack. The data science team are effective communicators, working in a highly collaborative team environment, creating tools, processes, and patterns to handle performance, scale, and availability, using data to accomplish key strategic business initiatives.
- Adapt existing tools and processes to handle performance, scale, availability, usability, accuracy, and monitoring.
- Build data expertise and guide data quality across multiple business areas.
- Provides input to the team on data quality.
- Build data solutions using open-source, homegrown and proprietary software that enables product and business teams to make data-driven decisions.
- Collaborate on strategy and roadmaps for building scalable data solutions and a scalable data warehouse environment.
- Maintain expertise in the Big Data ecosystem AWS Technological stack, including industry trends, strategies, and products.
- Provide leadership and direction through subject matter expertise.
- Demonstrate understanding of the business and close alignment to stakeholder needs.
- Collaborate effectively with other technology teams and architects to solve complex problems spanning their respective areas.
Knowledge, Skills, and Abilities
- Knowledge of Economics, Mathematics, Statistics, Computer Science, or other business/analytical discipline.
- Ambiguity - able to deal with low levels of ambiguity by bringing clarity to the problem and communicating plans toward a solution with both technical and non-technical people.
- Communication - able to talk, write, and listen effectively with business peers as well as junior team members.
- Self-directed - suggest changes to high-value process improvements, drives initiatives independently, maintains status updates, and delivers project work in a timely manner with little supervision.
- Technical Acumen - able to quickly understand and solve moderate complexity technical issues across multiple platforms, technologies, and paradigms.
- Business Acumen - understands key divisional business drivers, follows important game KPIs, and is familiar with key competitors.
- Analytical - exposure to basic statistical and machine learning techniques, a moderate degree of intellectual curiosity.
Experience working with multi-terabyte data sets using relational databases (RDBMS), SQL, and No-SQL.
Basic understanding of schedulers, workload management, availability, scalability, and distributed data platforms.
Developed large-scale analytical databases/platforms across multiple operating systems (Microsoft and Linux).
Experience in large-scale production software development using multiple languages.
Used agile/scrum methodologies to iterate quickly on product changes, developing user stories and working through backlogs.