Director of Business Intelligence & Reporting in London

ATG has two centres of data and analytics: a product analytics team (using Snowflake, Hex, TextQL, and Amplitude) and a commercial analytics capability within the sales organisation. Both are good at what they do. Neither produces the integrated performance view that the Board, executive team, and segment leaders need to run the business. This role exists to close that gap. You'll build the integration layer that connects financial data (from OneStream and our ERPs) with marketplace data (from Snowflake) and commercial data (from Salesforce CRM) into unified performance reporting. You'll own the KPI framework, build the tiered dashboards, and create the data infrastructure that transforms ATG's reporting from manually assembled spreadsheets into a connected, automated, insight-ready platform. This is not a traditional finance reporting role. You'll spend more time in Snowflake and Power BI than in Excel. You need to be as credible in a conversation with a data engineer about schema design as you are presenting a KPI dashboard to the Exec. The ideal candidate lives at the intersection of data and finance - and is frustrated by how rarely those two worlds connect properly.

Key Duties and Responsibilities

• Data Integration & Infrastructure
• Design and build the data pipelines that bring financial data (GL actuals, budgets, forecasts from OneStream) into ATG's Snowflake unified data model alongside existing product and commercial data.
• Extend the Snowflake UDM schema to accommodate financial data: fact tables for GL actuals, budgets, AR transactions; dimension tables for entity, segment, account hierarchy, and cost centre.
• Link Salesforce CRM data in Snowflake with financial data, enabling integrated views of auctioneer health (financial performance + CRM engagement + platform activity).
• Work alongside data engineering to configure TextQL to understand the financial data model, so the finance team and business leaders can query financial and marketplace data in natural language.
• Own data quality and reconciliation: financial data in Snowflake must reconcile to OneStream. Build automated checks and alert on discrepancies.
• Build strong working relationships with the product data team and the commercial analytics function. Invest time understanding their existing tools, workflows, and data assets before designing integration approaches — the goal is to connect and enhance what already exists, not replicate it.
• Own the KPI framework infrastructure: formalise metric definitions, establish baselines, and maintain the master KPI dictionary.
• Build tiered dashboards connected to Snowflake: Tier 3 operational dashboards for BU leads (daily/weekly, filterable by segment/platform/geography), Tier 2 executive dashboards with the full KPI hierarchy and drill-down capability.
• Design and implement automated alerts: flag when metrics cross defined thresholds and route to action owners via Teams.
• Enable self-service analytics for business unit leaders, reducing ad hoc data requests to the finance team.
• Reporting & Stakeholder Partnership
• Partner with the Director of FP&A to ensure the Board and executive reporting packs are backed by clean, automated data from the unified platform.
• Build genuine partnerships with the product data team (who use Hex on Snowflake) and the commercial analytics function. Understand their existing capabilities, workflows, and priorities so that the financial data layer connects to and enhances what they already produce — not competes with it.
• Partner with the commercial finance team to understand what data and reporting they need to deliver effective business partnering. The BI function exists to serve the finance team and the wider business — the priorities should be shaped by what decision-makers need, not what's technically interesting.
• Contribute the data and visualisation layer for investor materials, Capital Markets Day presentations, and strategic analysis.

Skills and Experience

• Significant experience (6–10+ years) in business intelligence, data analytics, or financial analytics, ideally in a technology, marketplace, or data-rich business.
• Strong hands‐on skills in SQL, Snowflake (or equivalent cloud data platforms), and data visualisation tools like Power BI, Tableau or Looker). You'll be building, not just directing.
• Experience designing data models and building ETL/ELT pipelines. You understand how to move data reliably from source systems into an analytical layer.
• Sufficient financial literacy to understand a P&L, balance sheet, and management reporting structure. You don't need to be a qualified accountant, but you need to know what questions the CFO and Board are asking and why the data needs to answer them.
• Experience working across data and finance teams — bridging the gap between technical data platforms and business-facing reporting.
• Comfortable with stakeholder management at senior levels. You'll present to the executive team and need to explain complex data concepts in business language.
• Strong lateral influence and relationship-building skills. You'll be working alongside established product and commercial data teams who have their own tools and ways of working. The ability to earn trust, build credibility, and align priorities with peers who don't report to you is essential.
• Familiarity with TextQL, Hex, Amplitude, or similar analytics tools is a strong advantage.
• Genuine enthusiasm for AI and automation. This role should be thinking about how to automate data pipelines, deploy AI-assisted anomaly detection, and build towards predictive analytics.

A Note on Background

We're open on whether this person comes from a data/analytics background with financial literacy, or a finance background with strong data skills. What matters is the ability to operate credibly in both worlds: you need to hold your own in a technical conversation about Snowflake schema design and in an Exec meeting about marketplace performance. The non-negotiables are hands‐on data skills, senior stakeholder credibility, and the ability to translate between data and business.