Senior Data Engineer

Responsibilities:

• Build the data foundation, bringing operational, product, commercial and contractual data into a single queryable layer, and decide the architecture and system of record for our core concepts: customer, site, deployment and contract
• Embed Dexory’s data security requirements into all foundational architecture and engineering work, ensuring security is a core design principle rather than an afterthought.
• Make customer and site performance answerable on demand by modelling perception accuracy, scan and mission performance, obstructions and scan coverage, connectivity and other operational signals against the SLAs and KPIs we have committed to per site.
• Define the metrics and business definitions with each team so that key terms are consistent and the data is trustworthy. Establish the metrics bible that controls the lens through which AI and reporting interpret our data. You facilitate and codify these definitions rather than owning every one alone.
• Use AI automation to join the dots between systems and to make data genuinely self-serve: connectors and pipelines where needed, and a trustworthy natural-language and query layer so teams get correct, context-aware answers instead of raw-data guesses.
• Partner with the engineering teams, platform, autonomy and perception, to have them expose source data cleanly, rather than building every pipeline yourself. Your focus is on what the data means and how it fits together.
• Own the ongoing health of the foundation: monitor pipelines, fix what breaks when sources change, and protect the trust that makes this the company's source of truth.
• Make pragmatic build-versus-buy decisions, set the engineering standards for the future team, and deliver early, visible wins within the first few months.
• Help define, recruit and mentor the team as the function grows.
• Required Qualifications:
• Significant experience as a senior data or analytics engineer, comfortable owning architecture and making source-of-truth decisions independently.
• Strong hands-on data skills: fluent SQL, solid data modelling, and a modern data stack. We are building on Databricks, so experience there or with an equivalent lakehouse or warehouse, plus a transformation framework such as dbt and strong Python, is what we are looking for.