Data Platform Architect & Engineering Lead

MotorK

Milano

In loco

EUR 72.000 - 88.000

Tempo pieno

6 giorni fa

Candidati tra i primi

Generatore di candidature

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Vantaggi offerti da questo lavoro

Meal vouchers

Flexible hybrid setup

26 days holiday

National holidays 30 days

Descrizione del lavoro

MotorK is hiring a Data Architect & Engineering Lead for an on-site, full-time role in Milano. You will own the data modeling architecture and drive the cloud data warehouse strategy across the platform, balancing scalability, performance, and maintainability.

You will lead a small team of two data engineers, implement dbt, Airflow and Airbyte pipelines, and partner with product and engineering to deliver robust data solutions. Salary from €80,000/year, with flexible growth opportunities.

Competenze

Deep, hands-on expertise in data modeling and data architecture.
Experience with a cloud data warehouse: BigQuery, Redshift, Snowflake or equivalent.
Hands-on experience with dbt, Airflow and Airbyte in real production environments.
Strong Python skills applied to data engineering pipelines and tooling.
Familiarity with modern data engineering concepts and AI-oriented direction.
Kafka or other streaming technologies is a strong plus.
Proven ability to technically lead engineers while remaining hands-on.
Clear communicator able to work with technical and non-technical stakeholders.
Bias to action and fast on delivering iteratively.

Mansioni

Own end-to-end data modeling architecture across the platform, balancing scalability, performance and maintainability.
Define and evolve the target architecture for data infrastructure and the roadmap to get there.
Bring modern data engineering practices into MotorK's data estate.
Manage and optimize the cloud data warehouse, owning performance, cost and reliability.
Design and build production-grade pipelines using dbt, Airflow and Airbyte with hands-on ownership.
Write production Python for pipeline development, tooling and automation.
Architect infrastructure supporting batch and streaming use cases (Kafka a plus).
Lead and mentor a team of 2 data engineers with code reviews and guidance.
Raise the bar on data quality, testing, documentation and delivery predictability.
Collaborate with product, engineering and business to translate requirements into data solutions.