Analytics Engineer
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About
Swan is the leading European fintech specialized in embedded banking. A laureate of the French government’s selective year list of tech champions, “French Tech Next 120,” we are quickly expanding across Europe.
Over 100 European companies have already seamlessly integrated banking services such as accounts, cards, and payments into their products through our Banking-as-a-Service platform. This approach, known as “embedded finance”, empowers businesses to elevate their offerings and create new revenue streams — often times tripling their revenue!
Our founders’ vision from the beginning was Simplicity: that anyone with a fintech idea at 2 am can visit our website, start building, and buy themselves a coffee with a self-issued card the very next day. That vision has taken us far.
Following a 38M€ Series B round last September, we have been doubling our headcount and already have over 230 Swanees across offices in Paris, Bordeaux, Berlin, Barcelona, Amsterdam, and Milan! If you’re excited about joining a European fintech adventure, Swan is the way!
To learn more about us: About Swan ; Our story.
Job description
Swan is looking for an Analytics Engineer to join its Data team. You will have a high-impact and high-exposure role within the organization. Your responsibilities will be the equivalent of a full-stack analytics professional, with emphasis on data modelling and occasional work on analysis and dashboard creation. This is an exciting opportunity to join a dynamic and growing team and make a significant impact on the future success of Swan.
Responsibilities
- Collaborate closely with other data team members, software engineers, and business stakeholders on a daily basis
- Develop and maintain robust and production-quality SQL pipelines for 1-2 business domains, adhering to engineering best practices and making sure the models are tested, documented and easy to use for data analysts, business users and financial regulators
- Become the data expert and main PoC for said business domains. Create reusable and scalable analytical solutions (datasets, dashboards, automations, etc) to empower your direct stakeholders and promote self-service data culture
- Help build the analytics engineering function by actively contributing to internal guidelines and best practices, suggesting process enhancement and adoption of new tools
- Keep up to date with latest industry standards and emerging tools
Preferred experience
Requirements:
- At least 3 years of experience in data field, with hands-on experience on data modelling
- Experience with DBT
- Strong proficiency using SQL in cloud data warehouses (e.g. BigQuery, Snowflake, Redshift)
Preferred Experience
- Previous experience in fintech industry and/or with a technical product
- Experience working with modern data stack technology, ideally during the setup and/or scaling phase
- Ability to dissect complex business problems, evaluate options, and implement production-quality solutions
- Comfortable navigating ambiguity and working in dynamic environments with minimal supervision
- A commitment to team spirit, transparency, and trustworthiness is important, as we value a collaborative and supportive company culture
- Passion, curiosity, and the capacity to learn quickly are important, as we are constantly exploring new technologies and approaches to improve our work
- Fluent in English. Swan is an international team, and you’ll be working in English with other Swanees on a daily basis
- Our ideal teammate: Empathetic. Skilled. Frank. We love to challenge each other, and we leave our egos at the door.
It’s okay if you don’t tick all the boxes — don’t let imposter syndrome prevent you from applying! 🙌
Swan is committed to providing a caring work environment for all employees, regardless of age, sex, disability, sexual orientation, race, religion, or belief.
When it comes to recruitment, we’re interested in your work experience, skills, and overall personality. Because diversity makes the workplace stronger and is necessary for Swan’s success, we are intensifying efforts to incorporate concrete actions to help us improve in this area.
About Swan
✨ Perks of being a Swanee:
- Hybrid remote policy: We offer the possibility of working from home for 2 days per week.
- The best health insurance: Alan 🦭
- Swan encourages you to have fun staying fit, thanks to partnerships with Classpass & Gymlib.
- We respect your lunch break. Mid-day free-time is sacred and our French office even provides a Swile card to cover your meal on work days. 🥪
- Twice a year we go somewhere gorgeous (a chateau, a mountain) where we reconnect, deep-dive into big topics, and relax.
- This isn’t a perk, it should be the rule, but diversity and inclusion are important at Swan. We’re working hard to get better every day.
✨ Our values:
Swan’s core values guide our actions daily. Individually, they may seem obvious, but together, they form a unique culture.
Simplicity: Leonardo Da Vinci said: “simplicity is the ultimate sophistication.” If something's convoluted or confusing, we work extra hard to break it down. - Making complex things simple is what we do.
Long Term: We always play the long game, whether it's to support our partners in their growth journey, or make tangible commitments to climate action.
Excellence: We are a team of experts who consistently go all out to create pixel-perfect banking services and exceed our partners' expectations— whatever it takes.
Be Human: We believe in the power of kindness and the importance of acting with integrity. But embracing our humanity extends beyond interpersonal interactions, it means caring about greater issues that affect our planet.
You can find out more about our culture.
Recruitment process
- A 30-min video call with our Talent Acquisition Manager, to get to know you, understand your career expectations and answer your questions
- A take-home technical test
- An interview with our Data Team
- An interview with Romain our VP Data
- An interview with our deputy CEO
- Department
- Data
- Locations
- Paris
- Remote status
- Temporarily Remote
Paris
Analytics Engineer
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