Data Staff Engineer
Pubblicato il 12-10-2026 - Motork in Bardi
OverviewIn this role you will own and shape MotorK's data platform, building data models, pipelines and warehouse architecture while guiding a small two-person data team.
You will set technical direction, maintain high engineering standards, and drive modern data practices across the platform.
You'll apply agentic AI concepts to automate workflows and enable scalable data solutions for our automotive SaaS business.
This is a hands-on, impact-driven leadership position with cross-functional collaboration.
Retribuzione / Benefitssalary from 80,000/year
meal vouchers
26 days holiday + national holidays
30 days/year to work from anywhere
flexible hybrid setup
room to grow nationally and internationally
ResponsabilitàOwn end-to-end data modeling architecture across the platform for scalability, performance and maintainability
Define the target data infrastructure architecture and the roadmap to reach it (warehouse, transformation, orchestration)
Introduce modern data engineering patterns and governance for the data estate
Manage and optimize cloud data warehouse performance, cost and reliability
Design and build production-grade pipelines with dbt, Airflow and Airbyte, with hands-on ownership
Write production Python for pipelines, tooling and automation
Architect support for both batch and streaming use cases (Kafka or similar)
Incorporate agentic AI into data platform architecture and operations
Lead, mentor and set technical direction for a 2-person data team through reviews and pairing
Raise quality standards: data quality, testing, documentation and delivery predictability
Collaborate with product, engineering and business stakeholders to translate requirements into robust data solutions
Requisiti fondamentaliDeep hands-on expertise in data modeling and data architecture
Production experience with cloud data warehouses (BigQuery, Redshift, Snowflake or equivalent)
Hands-on experience with dbt, Airflow and Airbyte in production
Strong Python skills for data engineering pipelines and tooling
Familiarity with modern data engineering concepts and AI trends
Kafka or other streaming technologies is a plus
Proven ability to lead engineers technically while remaining hands-on
Clear communicator with technical and non-technical stakeholders
Bias to action and fast iteration in the face of incomplete information
communication
mentorship and leadership
cross-functional collaboration
Cloud data warehouse expertise (BigQuery, Redshift, Snowflake)
DBT
Airflow