Senior Analytics Engineer - Monopoly Go!

Scopely is a leading video game and global interactive entertainment company, and they are seeking a product-minded Analytics Engineer who treats data as a first-class product. The role involves independently designing, building, and evolving data products while collaborating with various teams to ensure data quality and usability.

Responsibilities:

• Collaborate with engineers, product teams, and analysts to develop self-serve insight products that are responsive, precise, and scalable at petabyte levels
• Oversee the entire data product lifecycle, including designing new tracking plans, developing data models, ELT pipelines, and self-serve insight products like Looker explores and dashboards
• Act as a guardian of data quality, ensuring consistent metric reporting across a wide range of data products
• Establish and maintain robust data observability practices—including automated data validation, anomaly detection, SLAs, and alerting—to ensure trust and reliability across the pipeline
• Utilize cutting-edge technology stack including BigQuery, dbt and Looker
• Provide technical leadership and empathize with game product teams and departments to enhance their daily operations and product success
• Bring expertise in a specific part of the data stack and lifecycle while contributing broadly across all aspects
• Mentor team members and drive the adoption of best practices within the team
• Design data products with the end user in mind, prioritizing usability, discoverability, and long-term adoption across product and business teams
• Proactively identify gaps, risks, and opportunities in existing data products and instrumentation, and drive improvements with a product-ownership mindset

Requirements:

• A strong passion for solving complex analytical puzzles
• Proven ability to translate business needs into advanced analytics solutions
• Deep expertise with the modern data stack (BigQuery, Snowflake, dbt, Looker, Airflow, GitHub, command line-based workflows)
• Exceptional SQL skills coupled with at least 5 years of relevant experience in data analytics or engineering roles
• Solid understanding of data modeling principles (e.g., Kimball methodology, star schemas)
• Hands-on experience with data observability frameworks and data validation methods (e.g., dbt tests, schema testing, anomaly detection, SLAs/SLIs, lineage tools)
• A strong product mindset, with experience designing data products as user-facing solutions rather than one-off analyses
• Demonstrated ability to work effectively with cross-functional stakeholders, balancing technical constraints, business needs, and delivery timelines
• A high level of ownership and autonomy, with comfort operating in ambiguous problem spaces and proactively driving clarity and alignment
• Strong curiosity and experimentation mindset, with interest in exploring emerging technologies (including AI/ML and LLM-powered workflows) and applying them pragmatically to improve data products, analytics workflows, and stakeholder experience
• Enjoyment in working within fast-paced, growth-oriented environments