Why This Job is Featured on The SaaS Jobs
This Senior Analytics Engineer role stands out in SaaS because it sits at the intersection of product usage data and decision-making in a product-led platform. The remit—building canonical datasets, metric definitions, and trusted transformations—maps directly to how modern subscription businesses run: instrumentation, self-serve analytics, and consistent measurement across teams. The stated stack (dbt, Snowflake, Amplitude, Omni) reflects a contemporary analytics engineering approach geared toward scalable, reusable data products.
For a SaaS career, the long-term value is in owning the “analytics layer” that connects raw event data to product strategy. Work like data modeling for change, metric governance, and quality standards tends to compound over time, because it becomes the foundation for experimentation, retention analysis, and roadmap prioritisation. Experience enabling both human and machine consumption of data is also increasingly relevant as SaaS teams operationalise AI-assisted analysis.
This is best suited to someone who enjoys ambiguity-to-clarity work, partnering closely with Product and Engineering, and setting standards that others rely on. It fits professionals who want visible ownership, prefer building durable systems over one-off reporting, and are motivated by making analytics genuinely self-serve across a SaaS organisation.
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
Who are we?
From your everyday PowerPoint presentations to Hollywood movies, AI will transform the way we create and consume content. Today, people want to watch and listen, not read — both at home and at work. If you’re reading this and nodding, check out our brand video. Despite the clear preference for video, communication and knowledge sharing in the business environment are still dominated by text, largely because high-quality video production remains complex and challenging to scale—until now….
Meet Synthesia
We're on a mission to make video easy for everyone. Born in an AI lab, our AI video communications platform simplifies the entire video production process, making it easy for everyone, regardless of skill level, to create, collaborate, and share high-quality videos. Whether it's for delivering essential training to employees and customers or marketing products and services, Synthesia enables large organisations to communicate and share knowledge through video quickly and efficiently.
We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers and what 1,200+ people say on G2.In 2023, we were one of 7 European companies to reach unicorn status.
In 2023, we were one of 7 European companies to reach unicorn status. In February 2024, G2 named us the fastest-growing software company in the world and we announced our Series D in 2025. We've now raised over $330M from top-tier investors like NEA, Accel, Kleiner Perkins, Nvidia, and the founders of Stripe, Datadog, Miro, and Webflow.
Join the rocket ship while it's taking off! 🚀
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 4+ 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
