Senior Analytics Engineer – Fully Remote
il y a 2 semaines
Be part of a movement to change the way Europe pays
In today's digital world, payments often still feel outdated: random delays and confusing rules make it harder than it should be to pay and get paid. The European Payments Initiative (EPI) is here to change all that, forever.
With Wero, our digital wallet, we make sending and receiving money simple, seamless and secure across France, Belgium and Germany, with more countries and omnichannel solutions coming soon. Supported by 14 major banks and the two largest European acquirers, EPI is building a new, proudly European payment system: easy, instant and transparent, all for the greater good.
What's in it for you
Join us as a Senior Analytics Engineer and play a pivotal role in shaping our data landscape You'll design and implement scalable, high-quality data models, build robust ELT pipelines, and develop self-service data tools that empower teams across the organization
About the team
You'll be part of a Pan-European Product and Engineering team that operates in an Agile environment. You'll work closely — but fully remotely — with experts in Web Dev, Mobile Dev, Backend Dev, QA and DevOps from Germany, France, the Netherlands, Poland, and other European locations.
The sub-team you will join consists of a Product Owner, two Data Engineers, a Data Analyst and a Backend engineer.
Your impact
- Build high-quality and scalable data models that are business-driven and easy to query by our end users, enabling them to gain insights from data
- Maintain our data catalog, enabling easy data discovery for our end users
- Implement automated testing in our pipelines, so we find out about data quality issues before our end users do
- Develop ELT pipelines to onboard data onto a cloud data lakehouse
- Create and operate the infrastructure that makes analytics within EPI possible.
- Create tools and automations that allow platform users to discover and access datasets with ease
- Work closely with cross-functional teams including marketing, product, finance, and operations to support their analytics needs
- Provide training and support to end-users on how to use the EPI analytical data platform to gain insights
- Stay updated with the latest industry trends and best practices in data analytics and business intelligence
If you had joined us last month, here's what you could have done
- Built the data models that put WERO's transaction numbers into the spotlight —powering insights for its recent launch in France
- Tuned our data models like a race car to handle the surge in transactions and users—keeping costs low while keeping insights fast
- Kept a watchful eye on data inconsistencies —proactively monitoring and detecting issues before our users did, ensuring reliable and trustworthy insights from day one
Technology stack
- Primary: dbt, Databricks, Github
- Secondary: Terraform, MongoDB, AWS Kinesis
To succeed, you should meet at least 70% of these requirements
- 6 years of combined professional experience in analytics engineering, data engineering, and data analysis.
- Bachelor's degree in computer science, Statistics, Quantitative Economics, Engineering, or a related STEM field. A Master's degree is a plus.
- Fluent in English (CEFR C1 or C2) is mandatory; German, Dutch, French or any additional European languages is a plus
- Proficiency in languages such as SQL and Python and advanced experience with dbt
- Experience in data engineering using Databricks, Apache Spark, or similar systems
- Experience with collaborative CI/CD using GitHub
- Excellent data-oriented problem-solving skills and attention to detail
- Strong communication and presentation skills, with the ability to work independently and as part of a team
Nice to have:
- Previous experience in modeling data using Data Vault 2.0
- Prior experience in self-hosting data apps
- Experience in implementing data mesh architecture
???? If this looks like you, the recruitment steps are:
- A first call with one of our recruiters
- A Technical interview with our Data Engineers
- An interview with our Data Project Lead
- A final interview with our Head of Engineering
- Hopefully, an offer you can't refuse
Turn back if …
- You'd rather focus on exploratory analysis and storytelling than structuring data for self-service analytics
- You prefer working with well-established systems rather than experimenting with the latest technology and architectures
- You prefer a structured, predictable way of working over a fast-evolving environment where processes are still being shaped
Otherwise apply
???? Our commitment to equal employment opportunities
EPI offers the same job opportunities to all, without distinction of gender, ethnicity, religion, sexual orientation, social status, disability or age. EPI promotes the development of an inclusive work environment that mirrors the diversity of the clients our product is serving.
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