Senior Data Engineer

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 effortless for anyone, regardless of skill level, to create, collaborate, and share high-quality videos.

Whether it’s delivering essential training to employees, onboarding customers, or marketing products and services, Synthesia helps the world’s largest organizations communicate through video — quickly, easily, and at scale.

We’re trusted by leading brands like Heineken, Zoom, Xerox, and McDonald’s. See what our customers say and read over 1,200 reviews on G2.

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. In 2025, we announced our Series D. 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.

What will you be doing?

The Data team powers Synthesia’s R&D efforts by providing scalable, reliable, and observable data infrastructure for our Applied Research team. The Data team is responsible for all data needs, from ingestion to transformation, to modeling.

As a Data Engineer, you’ll take full ownership of pipelines that move and structure massive volumes of non-tabular video, audio, image, and text data across our lakehouse architecture.

You’ll work on high-throughput systems that enable internal teams to query and consume data more efficiently, and you’ll help drive the architecture, implementation, and observability of our entire data platform.

This is not a traditional data engineering role. It’s hands-on, hybrid, and high-impact, sitting at the intersection of research, infrastructure, and product. You’ll partner closely with R&D and infra teams, helping ensure that our systems scale with speed, performance, and cost in mind. We’re looking for someone who starts from the problem, not the tooling and knows how to build data systems around real-world use cases.

A few examples of what you might work on:

• Re-architecting our ingestion pipeline to better support long-form, high-resolution video data
• Implementing data tiering and modeling patterns like medallion architecture or dimensional modeling
• Host and manage open-source tools and frameworks
• Designing scalable observability for data quality and pipeline health
• Supporting researchers by enabling faster, more targeted data retrieval at training time

Who are you?

You're an experienced Data Engineer who loves building robust, reproducible, and scalable data systems and you care deeply about data quality, performance, and usability.

You’ll thrive in this role if you have:

• A track record of owning data pipelines end-to-end - from data sourcing and transformation through to modeling and observability
• Experience designing with data architecture patterns like lambda or kappa, and strong opinions on ETL vs ELT
• Familiarity with orchestration patterns (DAG-based, stateless, etc.) and workflow tools (we use Kubeflow and Spark)
• Strong SQL skills and experience building data models using patterns like dimensional or medallion architecture
• Hands-on experience with columnar formats and open table standards (Delta Lake, Iceberg, Hudi)
• Proficiency in Python and infrastructure tools like Terraform. Experience hosting open source frameworks

Bonus points if you have:

• Experience working in lakehouse environments or hybrid data architectures
• Exposure to GitOps practices or deploying infra on Kubernetes (we run on k8s but don’t expect deep k8s experience)
• Familiarity with the audio/video domain or non-tabular data workflows
• MLOps experience, such as model registry

Most importantly, you start with the problem & not the tech. You build data systems based on real use cases and are thoughtful about tradeoffs, complexity, and cost.

The good stuff...

• Very competitive compensation (salary + stock options + bonus)
• Hybrid work setting with an office in London, Amsterdam, Zurich, Munich, or remote in Europe. 
• 25 days of annual leave + public holidays
• Great company culture with the option to join regular planning and socials at our hubs
• A generous referral scheme 
• Strong opportunities for your career growth

You can see more about who we are and how we work here: https://www.synthesia.io/careers

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