Data Operations Engineer / Junior Data Architect
London – Hybrid
Fulltime
Industry: Banking/Asset Management/Investment Management
Working Hours: 8 per day/ 40 per week
Core Focus:
* A hands-on, all-round Data Operations specialist with architecture skills.
* Someone who can manage and run the data platform, especially during new asset acquisitions – ensuring data flows properly, systems function smoothly, and operations scale efficiently.
Experience Desired:
* Background in financial services or start-up environments (ideally both).
* Comfortable working across the full spectrum from Back Office to Front Office.
* Hybrid mindset – both technical and business-oriented.
* Experience working between Operations and Risk, understanding both the technology and business needs.
* Exposure to reporting, investment data, financial reports, and dataset nuances.
* Familiarity working in environments with little process – someone comfortable helping to define SOPs and build structure from scratch.
Tech Environment:
* Heavy on Microsoft stack: Dynamics, Power BI, Azure, Databricks.
* Data management and integration across systems, including financial reporting tools.
* Experience with low-code / no-code AI tools to drive operational efficiencies would be a major plus.
Responsibilities:
* Supporting the build-out and maintenance of the financial operations (FinOps) platform.
* Helping to set up internal and external reporting capabilities (particularly in Power BI).
* Supporting asset management platform development, including ingestion of climate data, market intel, and specialist datasets.
* Helping to migrate financial systems to Microsoft Dynamics.
* Acting as the “glue” across teams: Finance, Ops, Risk, and Tech – ensuring smooth data and operational flows.
* Bridging strategy and execution, especially with limited current systems in place.
Team & Structure:
* This is a standalone role, but part of a broader team of 15 under the COO.
* Working closely with operations, tax, finance, company secretary, and more.
Soft Skills / Traits:
* Innovative, self-starter, comfortable in ambiguity.
* Someone who can take initiative, bring structure, and drive forward data strategy.