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