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 youre reading this and nodding check out ourbrand video.
Despite the clear preference for video communication and knowledge sharing in the business environment are still dominated by text largely because highquality video production remains complex and challenging to scaleuntil now.
Meet Synthesia
Were 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 highquality videos.
Whether its delivering essential training to employees onboarding customers or marketing products and services Synthesia helps the worlds largest organizations communicate through video quickly easily and at scale.
Were trusted by leading brands like Heineken Zoom Xerox and McDonalds. See what our customers say and read over 1200 reviews on G2.
In 2023 we were one of 7 European companies to reach unicorn status. In February 2024 G2 named us the fastestgrowing software company in the world. In 2025 we announced our Series D. Weve now raised over $330M from toptier 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 Synthesias 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 youll take full ownership of pipelines that move and structure massive volumes of nontabular video audio image and text data across our lakehouse architecture.
Youll work on highthroughput systems that enable internal teams to query and consume data more efficiently and youll help drive the architecture implementation and observability of our entire data platform.
This is not a traditional data engineering role. Its handson hybrid and highimpact sitting at the intersection of research infrastructure and product. Youll partner closely with R&D and infra teams helping ensure that our systems scale with speed performance and cost in mind. Were looking for someone who starts from the problem not the tooling and knows how to build data systems around realworld use cases.
A few examples of what you might work on:
- Rearchitecting our ingestion pipeline to better support longform highresolution video data
- Implementing data tiering and modeling patterns like medallion architecture or dimensional modeling
- Host and manage opensource 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
Youre an experienced Data Engineer who loves building robust reproducible and scalable data systems and you care deeply about data quality performance and usability.
Youll thrive in this role if you have:
- A track record of owning data pipelines endtoend 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 (DAGbased 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
- Handson 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 dont expect deep k8s experience)
- Familiarity with the audio/video domain or nontabular 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
- other benefits depending on your location
You can see more about who we are and how we work here:https://www.synthesia/careers
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