Why This Job is Featured on The SaaS Jobs
This Senior Analytics Engineer role stands out in SaaS because it sits at the junction of product telemetry, decision-making, and the analytics layer that enables self-serve insight. With a clear product data focus and tooling that is common in modern SaaS stacks, the remit reflects how scaled subscription businesses operationalise metrics across teams. The emphasis on canonical datasets and metric foundations signals a company investing in consistency and trust as product usage data becomes a core asset.
From a career perspective, the work maps directly to high-leverage problems that recur across SaaS companies: defining durable metrics, building dbt models that survive product change, and establishing data quality expectations that stakeholders can rely on. Experience enabling tools like Amplitude and shaping how analytics is consumed across Product and Engineering is broadly transferable, especially for professionals who want to move between product analytics, data engineering, and data platform roles.
This position is best suited to someone who enjoys translating ambiguous product questions into maintainable models and is comfortable being a reference point for analytics engineering practices. It will fit professionals who prefer cross-functional partnering over ticket-driven delivery, and who want ownership over foundations rather than focusing solely on dashboards or one-off analysis.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US.
As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations.
Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow.
About the role
As an Analytics Engineer, you’ll be a key early member of our data function, responsible for building and evolving the analytics foundations that power product decision-making across the company. You’ll work closely with Product, Analytics, and Engineering to turn raw product data into trusted, well-defined datasets, metrics, and data products that scale with the business.
You’ll own the principles behind how we model data for self-serve and AI use cases, balancing speed with data quality and long-term maintainability. This includes designing models and metric foundations that are robust to change, easy to reason about, and suitable for both human and machine consumption.
What you’ll be doing
Partner with Product, Analytics, and Engineering to understand data needs and translate ambiguous questions into clear, scalable data models
Define, build, and maintain core dbt models that transform raw product data into canonical, well-documented datasets
Own metric definitions and transformation logic to ensure consistency, accuracy, and trust across reporting and analysis
Establish and uphold data quality standards, testing, and expectations around freshness and reliability
Work closely with Product Analysts to enable faster, higher-quality insights and decision-making
Support data consumption in tools like Amplitude and Omni, ensuring data is intuitive and easy to self-serve
Act as a subject-matter expert for analytics engineering, guiding best practices and helping others solve data problems
Contribute to shaping the future direction of our data stack as product complexity and scale increase
About the setup
⚒️ Stack: dbt, Snowflake, Amplitude, Omni
🌱 Early, high-impact role with real ownership over the analytics layer
🤝 Highly collaborative environment with product- and data-savvy stakeholders
🚀 Outcome-focused team where pragmatism and impact matter more than process
We’d love to hear from you if
You have 6+ years of experience in analytics engineering or data engineering, ideally in product-led or high-growth environments
You have strong hands-on experience with dbt and enjoy designing modular, scalable, and well-tested data models
You write advanced, performant, and maintainable SQL
You can translate business and product requirements into robust data pipelines and metrics
You have a strong product mindset and understand how data and metrics influence product direction
You’re comfortable operating across the stack and taking ownership end to end when needed
You care deeply about data quality, clarity, and trust
You’re outcome-driven and can clearly articulate the impact your work has had on teams or the business
Our culture
At Synthesia we’re passionate about building, not talking, planning or politicising. We strive to hire the smartest, kindest and most unrelenting people and let them do their best work without distractions.
Our work principles serve as our charter for how we make decisions, give feedback and structure our work to empower everyone to go as fast as possible. You can find out more about these principles here.
The good stuff...
📍A hybrid or remote-friendly environment for candidates based in Europe. You can work fully remote if you're not local to an office or hybrid from London, Amsterdam, Munich, Zurich or Copenhagen offices.
💸 A competitive salary + stock options
🏝️ 25 days of annual leave + public holidays (plus the option to take 5 days unpaid leave and carry 5 days over)
🥳 You will join an established company culture with optional regular socials and company retreats
🍼 Paid parental leave entitling primary caregivers to 16 weeks of full pay, and secondary 5 weeks of full pay
👉 You can participate in a generous recruitment referral scheme if you help us to hire
💻 The equipment you need to be successful in your role
You can see more about who we are and how we work here: https://www.synthesia.io/careers
