About the job
Join Synthesia, the premier AI video platform for enterprises, where over 90% of Fortune 100 companies leverage our innovative solutions. Founded in 2017 and headquartered in London, we have expanded our presence across Europe and the US, fostering a culture of creativity and collaboration.
As AI revolutionizes the workplace, we are committed to developing cutting-edge products that elevate visual communication and enhance organizational skill development, empowering individuals to thrive in high-performing teams.
After our successful Series E funding round, we proudly stand with a valuation of $4 billion, supported by over $530 million in funding from top-tier investors like Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, as well as the founders of Stripe, Datadog, Miro, and Webflow.
About the Role
As a Senior Analytics Engineer, you will play a vital role in shaping our data function from the ground up. Your expertise will drive the development and enhancement of analytics foundations that inform strategic product decisions across the organization. Collaborating closely with Product, Analytics, and Engineering teams, you will transform raw product data into reliable, well-defined datasets, metrics, and scalable data products.
You will establish the principles for modeling data applicable to both self-serve and AI use cases, ensuring a careful equilibrium between speed, data quality, and long-term sustainability. Your responsibilities will include designing robust models and metric foundations that adapt to change, are easily understandable, and cater to both human and machine consumption.
What You’ll Be Doing
Collaborate with Product, Analytics, and Engineering teams to identify data needs and convert ambiguous inquiries into clear, scalable data models.
Define, construct, and maintain core dbt models that convert raw product data into authoritative, well-documented datasets.
Own metric definitions and transformation logic to guarantee consistency, accuracy, and trust across all reporting and analysis.
Establish and uphold data quality standards, testing, and expectations regarding data freshness and reliability.
Work in tandem with Product Analysts to facilitate quicker and higher-quality insights and decision-making processes.
Support data accessibility in tools like Amplitude and Omni, ensuring data is user-friendly and easy to self-serve.
Act as a subject-matter expert in analytics engineering, guiding best practices and assisting colleagues in solving data-related challenges.
Contribute to the strategic evolution of our data stack as we scale and increase product complexity.

