Data Team

We are looking for our future colleague to help us increase our Data team, part of engineering department and mainly in charge of:

• Handle an infrastructure with different technologies to provide a data platform (storage, computation, orchestration, visualisation):

  • A data lake house containing for instance vehicle telemetry data, vehicle uploads, etc.

  • Various data access tools: static reporting, dynamic dashboards, APIs, etc.

• Implement decided data governance rules (retention, segregation, etc.).

• Support stakeholders on data analysis.

• Evangelise on data usage and strategy.

Position details

Your future responsibilities is to ensure current data platform reliability (performance, availability, security) and usability with optimal costs by:

• Handling the data platform lifecycle from development to operation & maintenance including end user support.

• Participating in various team activities and developments linked to our data platform (extraction, storage, cleaning, organisation, transformation, orchestration, visualisation, etc.).

Main technical stack

• Apache Spark

• Trino

• Pandas / DuckDB / Apache Arrow

• Apache Parquet / Delta.io

• Apache Superset

• Argo Workflow

There is no typical profile at EasyMile, we all come from different backgrounds and that is what makes us strong! Don’t hesitate to apply if you are motivated and interested by innovative transportation and technologies.

We are looking for a 5-10 years XP in order to develop and maintain our data platform (from infrastructure to end user application) :

• Application deployment (Kubernetes / Helm preferred) - Advanced

• Programming languages (full stack: scala / python; typescript / react; APIs) - Advanced

• Continuous Integration & Development (GitLabCI preferred) - Advanced

• Cloud Providers (AWS / terraform preferred) - Intermediate

• English - Advanced 

Desirable:

• Experience in data oriented application development

• Knowledge on data pipelines, messaging or database systems

• 30 minutes call with the recruitment team

• 1 case-study with the Data Architect

• One hour interview with the manager and the recruitment manager