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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