Analytics Engineer

at  SLAY

SLAY, founded in December 2022, has swiftly made its mark in the mobile world. In 2023, we developed several apps and games that reached the #1 spot in the App Store across 3 continents.
Backed by some of the world’s most esteemed investors, including Accel, Kevin Weil, Riccardo Zacconi Scott Belsky, and Ilkka Paananen, SLAY is rapidly growing and reaching millions of users.
Our mission is to create digital life through AI and become the leading company for virtual friends that live, grow and evolve like humans—starting with Pengu. Pengu has become the biggest AI character app with its own IP in the US and Europe.

Tasks

• Data Analysis and Insights: Enable tactical and strategic decision-making by providing insightful analyses, developing models, and creating dashboards.
• Develop and Maintain Data Pipelines: Build robust and scalable transformation pipelines in dbt to support our high data volume of 500k daily active users, employing engineering best practices.
• A/B Testing: Design, analyze, and interpret the results of A/B tests to inform product and marketing strategies.
• Cross-functional Collaboration: Work closely with various teams to understand their data needs and deliver solutions that drive business objectives.
• Process Improvement: Continuously seek opportunities to optimize data processes and workflows for efficiency and scalability.

Requirements

• Experience: 3+ years in a role such as Data Engineer, Analytics Engineer, or Data Analyst.
• Technical Proficiency: Strong expertise in SQL and experience with cloud data warehouses.
• Version Control: Experience working with Git for version control.
• Workflow Orchestration: Familiarity with workflow orchestration tools.
• Programming Skills: Proficiency in a programming language (e.g., Python) is a plus.
• Adaptability: Proven ability to deliver high-quality results in a fast-paced, high-pressure environment.
• Analytical Mindset: Strong problem-solving skills and a data-driven approach.
• Communication Skills: Excellent verbal and written communication skills, with the ability to convey complex data insights to non-technical stakeholders.

• Data Analysis and Insights: Enable tactical and strategic decision-making by providing insightful analyses, developing models, and creating dashboards.
• Develop and Maintain Data Pipelines: Build robust and scalable transformation pipelines in dbt to support our high data volume of 500k daily active users, employing engineering best practices.
• A/B Testing: Design, analyze, and interpret the results of A/B tests to inform product and marketing strategies.
• Cross-functional Collaboration: Work closely with various teams to understand their data needs and deliver solutions that drive business objectives.
• Process Improvement: Continuously seek opportunities to optimize data processes and workflows for efficiency and scalability