Engineer focusing on data engineering in Google Cloud Platform. Developing and maintaining data pipelines with governance on information quality.
About the role
- Data Engineer designing robust data platforms for advanced AI and machine learning applications. Collaborating with teams to improve data engineering practices in a tech-focused scale-up.
Responsibilities
- Design and implement large-scale data ingestion, transformation, and exposure pipelines
- Define and implement high-performance data architectures (data lake, data warehouse, lakehouse, analytics platforms)
- Productionize solutions that incorporate machine learning or AI models
- Participate in technology selection and evolution of the data ecosystem
- Mentor and provide technical guidance to other data engineers
- Contribute to engineering best practices (code reviews, documentation, quality, security)
- Regularly interact with product teams, business stakeholders, and occasionally end customers
- Take part in cross-functional initiatives: R&D, continuous improvement, internal tooling, training, automation
Requirements
- Strong mastery of at least one programming language (Python, Java, Scala, Kotlin, etc.)
- High proficiency in SQL
- Solid understanding of data processing paradigms (batch, streaming, messaging, caching)
- Good knowledge of storage systems (relational databases, NoSQL, data warehouses, data lakes)
- Daily use of Git and CI/CD pipelines
- Experience with containerization (Docker)
Benefits
- Meal vouchers (tickets restaurant)
- Flexible hybrid remote work
- Navigo pass (public transport pass)
- Training budget and support for attending tech conferences
- Friendly work atmosphere and regular internal events
- Stimulating technical environment
- Varied, high-impact projects
- Opportunities to grow into expert or technical leadership roles
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