Data Engineer at Proton

Barcelona, Catalonia, Spain -

Full Time

Start Date

Immediate

Expiry Date

26 Jan, 26

Salary

0.0

Posted On

28 Oct, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Backend Engineering, Kafka, Spark, Python, Scala, SQL, ClickHouse, Docker, Kubernetes, GitLab CI, Data Quality, Observability, Airflow, ML Pipelines, APIs

Industry

technology;Information and Internet

Description

Join Proton and build a better internet where privacy is the default At Proton, we believe that privacy is a fundamental human right and the cornerstone of democracy. Since our inception in 2014, founded by a team of scientists from CERN, we have dedicated ourselves to providing free and open-source technology to millions worldwide, ensuring access to privacy, security, and freedom online. Our journey began with Proton Mail, the largest secure email service globally, and has since expanded to include Proton VPN, Proton Calendar, Proton Drive, and Proton Pass. These tools empower individuals and organizations to take control of their personal data, break away from Big Tech’s invasive practices, and defeat censorship. Our work impacts hundreds of millions of lives, from activists on the front lines defending freedom to leaders in governments protecting sensitive information. In some cases, Proton’s services have even been instrumental in saving lives by enabling secure and private communications in high-risk situations. Proton is a profitable company that does not rely upon VC funding, supporting over 100 million user accounts with a growing team of over 500 people from over 50 different countries, from the world's top companies and universities. We value intelligence, learning potential, and ambition in our hiring process. Adaptability is key as we navigate uncharted territories and redefine how business is conducted online. Hiring at Proton is highly selective, with less than 1% of candidates hired. We believe smaller teams of exceptional talent will always prevail over larger teams with lower talent density. You will have the opportunity work with many of the world's top minds in their fields, ranging from former international math and science olympiad winners to chess champions. We have a global mindset and big ambitions but remain a start-up at heart. We value empowerment and flexibility and keep our structure flat to keep moving fast and avoid unnecessary politics. Tired of blending into the crowd? Join us and do work you can truly be proud of. Check our open-source projects here! Purpose of the role The Proton Data Platform team is responsible for everything that enables the company to make data-driven decisions, with our on-premise, custom data platform at the center. We are looking for a Data Engineer to join the team and help building and maintaining reliable batch and streaming data pipelines and tools, learn best practices for data modeling and quality, and support analytics/ML use cases. You’ll work with mentors on the team and grow into owning pipelines end-to-end. What you will do Implement and maintain ingestion & transformation jobs (Kafka → Spark), with guidance. Write clean, testable code in Scala and Python for data pipelines and utilities. Query and optimize datasets in ClickHouse SQL (partitioning, basic tuning). Add data quality checks and monitoring; help triage pipeline issues. Contribute to CI/CD and containerized jobs (Docker, GitLab CI; exposure to Kubernetes). Collaborate with analysts/ML engineers to turn requirements into well-scoped tasks. Document workflows and share learnings in code reviews and short design notes. Job requirements ~1–3 years in data engineering or backend engineering with data-heavy systems (internships or projects count). Solid software engineering foundations: version control, testing, code reviews, readable code. Working knowledge of one of: Kafka or another streaming system; Spark or another distributed compute engine. Proficiency in Python; willingness to learn Scala (or vice versa). Comfortable with SQL; curiosity to learn ClickHouse specifics. Clear communication, ownership mindset, and eagerness to learn. Bonus points for: Exposure to ClickHouse (engines, table layouts, partitioning). Python data stack: pandas, matplotlib, dask. Data quality/governance tools (e.g., Great Expectations, DBT tests) and basic lineage/metadata. Infra & DevOps basics: Docker, Kubernetes, GitLab CI; observability (Prometheus/Grafana). Orchestration tools (Airflow, Dagster, Argo) and feature/ML pipelines. Experience with payment providers APIs and ChargeBee. What We Offer Office First: Collaboration is easier and more effective in person, which is why we have offices in Geneva, Zurich, Prague, Barcelona, Paris, London, Vilnius, Skopje, and Taipei. You can also enjoy working from home up to 30% of the time, while enjoying great company during our three core days in the office. Technology: We provide all the devices and software you need to excel in your role, ensuring you have the best tools at your disposal to achieve your goals. Food: Lunch and snacks are provided by Proton every day at our offices. Transport: We will always support our employees with transport costs through subsidizing public transport, bike allowances, or parking spaces based on your office location. Stock Options: At Proton, we are all owners of the company and you get stock options when you join us. Flexible Working: You can define your own working hours as long as it works with team meetings. Learning and Development: We are committed to your professional growth. Proton offers various learning opportunities, including training programs, conferences and events, and continual learning. Employee Benefits: Comprehensive health insurance plans, competitive retirement savings options, generous vacation and leave policies, and wellness programs. Work that Matters: Proton is a community-first organization, started with the support of a crowdfunding campaign and built with community input. To this day, Proton’s only source of revenue is user subscriptions. Over 100 million people trust and support Proton, and we put our users and community first in everything we do. Read more about our impact here. Our Commitment to Diversity and Inclusion At Proton, we believe diversity drives innovation and strengthens our mission to provide privacy as a default for all. We are committed to fostering an inclusive environment where all individuals, regardless of race, ethnicity, gender, age, sexual orientation, physical ability, or socio-economic background, feel valued and empowered. We strive to create equal opportunities, promote open dialogue, and support continuous learning to ensure every voice is heard and respected. If you need any extra support or reasonable adjustments during the hiring process, please let your talent partner know. Candidate Privacy Notice When you apply for a position, refer a candidate, or are considered for a role at Proton Technologies AG (Proton, we, us, or our), your information is stored in Greenhouse, in accordance with their Service Privacy Policy. This information is used to evaluate your suitability for the posted position. We also retain this information for consideration for future roles that you may apply for or that we believe may align with your background and skills. If we no longer have a legitimate business need to process your information, we will either delete or anonymize it. Should you have any inquiries about how we use or manage your information, or if you wish to access, correct, or delete your data, please contact our privacy team at careers@proton.ch. Proton does not accept unsolicited resumes from any sources other than directly from candidates. We will not pay a fee for any placement resulting from an unsolicited offer, even if the candidate is subsequently hired by Proton. To learn more about our privacy policy, please visit our privacy policy page. #LI-ONSITE

Responsibilities

The Data Engineer will implement and maintain ingestion and transformation jobs, and write clean, testable code for data pipelines. They will also collaborate with analysts and ML engineers to turn requirements into well-scoped tasks.