Lead Data Engineer

Join to apply for the Lead Data Engineer role at Genies

Join to apply for the Lead Data Engineer role at Genies

Genies is an AI avatar and games technology company powering the next generation of digital experiences through Smart Avatars. Genies' technology stack is rooted in empowering user generated content through the company's two main mantras: “Anyone can create anything” & “Everything works with everything”. By combining these two guiding principles, individuals can craft limitless experiences while IP owners can build dynamic social gaming ecosystems powered by user-generated content (UGC) and AI Avatars—what Genies calls "Parties." Genies' technology stack features a comprehensive suite of UGC tools that enable anyone to create AI avatars, complete with customizable fashion, props, behaviors, and personalities, as well as immersive AI avatar experiences. At its core is the Genies Avatar Framework, which leverages machine learning and computer graphics to ensure seamless interoperability across all user-generated AI avatars and experiences—unlocking boundless creative potential. Early adopters of Genies’ first gen avatars include icons like Justin Bieber, Rihanna, J Balvin, Migos, and thousands more. With offices in Los Angeles and San Francisco, Genies has raised $200M from notable investors including Silver Lake, BOND, NEA, and Bob Iger. We are seeking a Lead Data Engineer who is passionate about building the foundational data infrastructure that empowers teams to make smarter decisions and deliver exceptional user experiences. In this hands-on leadership role, you will define how events are structured and organized while collaborating with product stakeholders to ensure clarity and alignment. You will design our data storage architecture, select the right systems and tools to enable business teams, and build high-quality pipelines that make data reliable and accessible. Responsibilities include owning the definition and management of event structures, designing and maintaining event taxonomies, naming conventions, and guidelines, collaborating with product stakeholders, defining data storage architecture, evaluating and implementing storage solutions such as data warehouses, lakes, or transactional stores focusing on scalability, reliability, security, and cost-effectiveness. Lead decision making on data usage to empower business teams, assess and recommend analytics platforms, build and maintain robust, performant, and secure data pipelines and ETL processes, mentor and provide technical leadership to other engineers, and establish best practices for data modeling, testing, monitoring, and documentation. Requirements include 5+ years of experience in data engineering or related field, strong experience with data pipelines using orchestration frameworks like Airflow or Dagster, expertise in SQL, data modeling, schema design for analytical workloads, familiarity with cloud-based data storage solutions like Snowflake, BigQuery, Redshift, experience with third-party analytics platforms like Mixpanel or Amplitude, excellent communication and collaboration skills, proven ability to define and manage event tracking structures, leadership experience mentoring engineers, and ideally experience in growth stage companies. Benefits include professional development support, flexible hours, work from home policy, startup culture with stability, comprehensive health insurance, competitive salaries, unlimited paid time off and other leaves, health & wellness support, modern office space, and choice of MacBook or Windows laptop.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  Software Development

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