Join an AI-first data team focused on building reliable, scalable data pipelines.. Design and maintain core data infrastructure to support diverse data use cases.. Enable real-time analytics and AI-driven decision-making across the company.
Responsibilities
- Design, build, and maintain foundational data infrastructure components that support a wide range of data applications.
- Improve the data stack with enhanced lineage tracking, monitoring, and alerting to prevent data incidents and ensure high data quality.
- Apply best practices in data management, storage, and security to maintain data integrity and regulatory compliance.
- Own the primary company data pipeline, translating business requirements into efficient and dependable data workflows.
- Contribute to code reviews to uphold code quality and facilitate knowledge sharing across teams.
- Lead evaluations and integrations of new technologies and tools to strengthen data infrastructure capabilities.
- Define and oversee evolving data models and schemas, ensuring SLAs for datasets that underpin key business metrics.
- Work closely with applied scientists, data scientists, analysts, and business teams to streamline data processing, storage, and orchestration for greater efficiency.
Requirements
- Bachelor's degree or higher in Computer Science, Engineering, or a related discipline.
- Minimum of 3 years of experience in data engineering with a focus on building and maintaining data pipelines and infrastructure.
- Strong proficiency in SQL and Python, with the ability to write efficient, scalable code for complex data tasks.
- Hands-on experience with data workflow tools such as dbt and Airflow.
- Solid understanding of distributed computing concepts and practical experience with cloud data platforms including AWS, GCP, or Azure.
- Strong analytical and problem-solving abilities, with a track record of resolving complex data challenges.
- Excellent communication and collaboration skills, with experience working in cross-functional environments.
Nice to Have
- Experience designing AI-ready semantic data layers, particularly for enabling low-latency, high-fidelity analytics at scale.
- Familiarity with data governance, data privacy, business intelligence tools, and data platform tooling is advantageous.
Tech Stack
SQL, Python, dbt, Airflow, AWS, GCP, Azure
Benefits
- Competitive salary and equity compensation
- Full coverage of medical, dental, and vision insurance
- 401k plan with company matching
- Unlimited paid time off to support personal well-being
- Reimbursements for wellness, internet, and childcare expenses
- Generous parental leave policy
- Commitment to work-life balance
- Fast-paced learning environment with an entrepreneurial mindset and strong team collaboration
- Diverse, multicultural workforce with representation from over 45 nationalities
Compensation
Competitive salary package. Equity: equity. The actual salary offered will carefully consider a wide range of factors, including your skills, qualifications, and experience.
Work Arrangement
local-city — Paris, Seattle, Madrid, London, Berlin, San Francisco, New York City, Sydney, Mexico City — not specified
Team
Part of the Data Engineering team, working alongside Data Science, Analytics, and Applied Scientists within a larger data organization
- customer-obsessed
- data-driven
- focused on delivering meaningful outcomes
- values ownership
- continuous learning
- thoughtful speed
- collaborative
- fast-moving
- trust and impact matter
Additional Information
- Headquartered in Paris, with a strong North American presence based in Seattle.
- Teams operate across Madrid, London, Berlin, San Francisco, New York City, Sydney, and Mexico City.
- Diversity, equity, and inclusion—regardless of origins, identity, background, or orientations—are central to the company's mission.
- Active inclusion is promoted to create a strong sense of belonging for all employees.
- Committed to ensuring everyone has a seat at the table and is valued, respected, and given equal opportunities to grow and succeed.
