NEO is seeking a hands-on Data Platform Engineer to design and deliver enablement for our Modern Data Platform (Airbyte, Dagster, dbt, Azure Databricks, SODA, Power BI, GitHub). This person will empower data teams, create reusable training assets, and help drive adoption as part of the Center of Excellence.

Key responsibilities:

• Design and deliver training sessions for all Modern Data Platform components, ranging from introductory to advanced.
• Develop hands-on labs, quickstart guides, templates, and reusable enablement materials to accelerate onboarding and adoption.
• Act as the main point of contact for questions related to the Modern Data Platform.
• Analyze and implement use cases: process demand requests, translate requirements into platform solutions, and support end‑to‑end delivery.
• Potentially be delegated to a data team to provide hands-on assistance during implementations.
• Embed governance, security, and access best practices into all training content and platform guidance.
• Operate and grow the community of practice: host office hours, facilitate user groups, and publish enablement resources.
• Measure and report on training effectiveness, user engagement, and overall platform adoption.
• Collaborate closely with platform engineering and governance teams to align enablement with evolving technical and compliance standards.
• Identify opportunities to improve the Modern Data Platform and contribute to ongoing enhancements where needed.

Profile:

The candidate must be able to demonstrate recent and proven experience in promoting technical excellence in Databricks, as well as in developing a strong culture of knowledge sharing and developing strategic partnerships.

The candidate must be able to demonstrate recent and successful experience in supporting a data journey from strategy to value as well as in implementing a data pipeline.

You have recent and successful experience as a data engineer, data analyst, cloud engineer, DevOps engineer or software developer.

Along with your CV, we ask that you include the answer to the next question (the absence or insufficiency of a response is eliminatory): How have you worked with Airbyte and Databricks in the past? Please give a concrete example.