Data Engineer
Seeking a Data Engineer to build and maintain scalable data pipelines and models that support Product, Finance, Operations, and R&D teams. You will translate business needs into robust data solutions, ensuring data quality and reliability across the organization.
Responsibilities
- Design and build end-to-end data pipelines, from source structures and API integrations to clean, trusted datasets for analytics and reporting.
- Translate business requirements into scalable data solutions, aligning with product roadmaps and business priorities.
- Act as a technical partner for cross-functional teams, delivering data models, pipelines, and internal tools.
- Write high-quality, maintainable code following best practices and modern data tooling, including CI/CD.
- Monitor, validate, and troubleshoot data quality and pipeline reliability, driving continuous improvement.
Requirements
- B.A./B.Sc. in a highly quantitative field.
- 4+ years of hands-on data engineering experience, including building data pipelines, writing complex SQL, and structuring data at scale.
- Fast learner with high attention to detail, strong ownership, and ability to manage multiple priorities in a dynamic environment.
- Strong communication skills to partner effectively with technical and business stakeholders.
- Experience with Google Cloud data technologies (BigQuery, Cloud Composer/Airflow, Pub/Sub, Cloud Functions) or equivalent AWS/Azure services.
- Hands-on experience with dbt for data transformation and modeling.
- Practical experience using AI tools (e.g., Claude, Cursor, GitHub Copilot) to improve development workflows.
- High business intuition and analytical mindset, with ability to turn raw data into insights and impact.
- Fluent English and experience working with global teams.
Nice to have
- Experience designing and building scalable data systems for various data applications.
- Background in data-driven companies in large-scale environments.