Meet DeepL

DeepL is a global communications platform powered by Language AI. Since 2017, we’ve been on a mission to break down language barriers. Our human-sounding translations and intelligent writing suggestions are designed with enterprise security in mind. Today, they enable over 100,000 businesses to transform communications, reach new markets, and improve productivity. And, empower millions of individuals worldwide to make sense of the world and express their ideas.What Sets Us Apart

What sets us apart is our blend of modern technology, competitive benefits, and an open, welcoming work culture that enables our people to thrive. This may be because of our products that have helped countless people worldwide or our shared mission to improve communication for individuals and businesses, bringing cultures closer together. Being part of DeepL means joining a team dedicated to innovation and employee well-being.Meet the team behind this journey

DeepL has millions of passionate users around the globe, both consumer and enterprise. The Data Foundation team increases operational efficiency and drives innovation at DeepL by facilitating the flow of data from producers to consumers, to maximize business impact. We create stable and user-friendly analytical data products, making customer data models and user behavioral data accessible and reusable for data-driven professionals throughout the company.In this role, your main responsibilities and deliverables will be to build and maintain data pipelines, create foundational data models in our data warehouse, and integrate new data sources using DataOps best practices, including documentation and testing. You will also support other data specialists to ensure queries and tables are efficient and data is used effectively.Your ResponsibilitiesData pipeline development: design, implement, and maintain scalable data pipelines and architecture in both on-prem and cloud environments. Build the next generation of DeepL\''s data products while maintaining and migrating legacy assets.Data modeling: develop and optimize data models to support analytics and reporting needs, ensuring data quality, consistency and integrity.Collaboration: work closely with data scientists, product analysts, and business stakeholders to understand data requirements and deliver solutions.Performance optimization: monitor and enhance the performance of data systems, ensuring low latency and high reliability.Data quality: own the quality and availability of our data. Apply data governance frameworks and champion data contracts to guarantee confidence in analytics datasets.Documentation and best practices: maintain comprehensive documentation and promote best practices in data engineering and analytics.Mentorship: guide and mentor junior team members, fostering a culture of continuous learning and improvement.Qualifications / What We Look ForExperience: 5+ years in data or analytics engineering roles, with a focus on cloud data platforms.Data Modeling: Expertise in designing and implementing data models for analytics.SQL: Advanced proficiency in writing complex queries and optimizing performance.Python: Experience in data manipulation and scripting.Cloud Platforms: Hands-on experience with cloud data warehouses like Snowflake, Databricks, or BigQuery. Experience with an on-prem data warehouse such as ClickHouse is valuable.Data orchestration: Experience with tools like dbt, Airflow, or similar.OLAP / real-time processing: Understand best practices for querying OLAP, clickstream, and real-time event processing databases.Product mindset: Ability to work with business stakeholders to translate analytics needs into user-friendly, high-performance data products.Troubleshooter: Experience diagnosing and resolving data issues and outages; willingness to participate in on-call rotations and perform post-mortems.Soft Skills: Excellent problem-solving abilities, strong communication, and a collaborative mindset.What We OfferDiverse and internationally distributed team: join a global community with people of more than 90 nationalities.Open communication and regular feedback: clear, honest communication and constructive feedback.Hybrid work and flexible hours: office twice a week with flexibility to work remotely; aligned with team locations and time zones.Regular in-person team events and monthly hacking sessions: opportunities to collaborate across teams and explore initiatives.Leave and benefits: 30 days of annual leave; comprehensive benefits tailored to your location.Equal Opportunity

We are an equal opportunity employer. You are welcome at DeepL for who you are—we appreciate authenticity here. Our product is for everyone, and so is our workplace. The more voices represented, the more we will all succeed, contribute, and think forward. Bring your personal experience, perspectives, and background. Diversity drives our ability to break down language barriers.

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