• Expert-level analytical and problem-solving skills, with a demonstrated ability to tackle highly complex data challenges
• Deep understanding of statistical methods and techniques, with the ability to develop and apply advanced analytical models
• Exceptional communication and presentation abilities, with the capability to communicate complex insights to diverse audiences, including senior leadership
• Strong leadership and mentoring skills, with the ability to lead large analytical projects and provide guidance to junior analysts
• A life-long learner who is curious, has a passion for solving hard, ill-defined problems, has comfort taking initiative and who continuously seeks to improve their skills and understanding
• 8+ years of professional experience as a hands-on, analytics / business intelligence engineer
• Ability to think strategically and initiate, refine and complete projects proactively with minimal guidance and to supervise data analysts, data engineers and data scientists with their projects
• Expert knowledge building complex, scalable cloud-based systems, data pipelines, and data modeling
• Expert knowledge of SQL, data modeling, ETL development, and data warehousing
• Expert knowledge of analytics/BI tool architecture, functions, and features
• Strong Python skills for data analysis and visualization
• Experience designing analytics/BI architecture to power a variety of uses cases, including machine learning, data analytics and visualization
• Ability to work with large data sets and optimize performance of analytical solutions
• Experience with compliance, audit, user access control process and data governance
• Demonstrated leadership and self-direction. Willingness to both teach others and learn new techniques
• Experience in project management and Agile delivery methods

Desirable

• The Business Intelligence and Data Science Enablement team's mission is to provide advanced analytical insights and capabilities to inspire and optimize the future direction of the business
• Our team is building an internal self service data platform that encompasses collection, processing, visualization, analysis, anomaly detection, root case and predictive modeling for both qualitative and quantitative data from all our users.
• We specialize in game streaming telemetry and prepare highly sophisticated analysis with real time intelligence captured to highlight paths of improvement for the quality of experience
• As a Staff BI Analyst/ Staff Analytic Engineer within our team, you'll harness the potential of data to empower us in providing unparalleled cloud streaming performance and delivering exceptional experiences to our players across the world
• Collaborate with cross-functional teams to develop actionable recommendations and contribute to the achievement of organizational objectives
• Responsible for leading major analytical projects, designing and implementing analytical methodologies, providing guidance on complex data issues, and contributing to the development of organizational strategies
• Participate in high-level decision-making processes, provide guidance to senior management, and influence strategic directions based on their deep analytical expertise and insights
• Develop new analytical methodologies, lead research initiatives, and tackle strategic issues that have a significant impact on the organization's long-term success
• Leadership responsibilities and possibly overseeing teams of analysts, data scientists or researchers
• Serve as the Analytics data lead working with the centralized data teams to optimize data pipelines and common data models in Snowflake/Databricks and S3/Kafka
• Be a champion of “data as a product” and strive to build robust and scalable data products
• Use your advanced data skills building data models for consumption by a team of data engineers, data scientists, data analysts, and our internal data consumers
• Build ad-hoc SQL queries, pipelines and notebooks as needed to support projects and complex business analysis
• Implement procedures and standards around data reliability, accuracy, and availability
• Implement DataOps best practices for versioning, testing, and production support
• Improve data literacy through documentation and data consumer training
• Tech Stack: Snowflake, Databricks, OpenSearch, DBT, SQL, Python, GitHub/Gitlab, Airflow, Kafka
• Be the team architect and champion for the business intelligence tools/ analytics tools
• Develop best practices, standards, and optimization of the different tools for specific use cases
• Lead the complex engineering efforts to build dashboards and data visualizations that create valuable insights supporting business decisions
• Compose business and technical documentation to improve data literacy across the organization lifting the self-service analytical capabilities of our stakeholders
• Tech Stack: Domo, Imply, Databricks, MicroStrategy, Streamlit