• Build and maintain dbt models that transform source data into clean, tested datasets for analytics and reporting. • Write SQL to investigate data issues, validate new sources, and answer stakeholder questions with accurate, reproducible logic. • Implement data quality checks (dbt tests, freshness, reconciliations) and help resolve production data issues, including on-call rotation. • Document models, metrics, and lineage so teammates and stakeholders understand definitions and dependencies. • Partner with analysts and business teams to deliver production-ready data products—not just ad hoc queries. • Use modern tooling—including AI-assisted frameworks—to move faster while keeping quality and review standards high.

• Business Intelligence Strategy: Translate the client's business objectives into effective information management and data intelligence strategies. • Pipeline Engineering (ETL): Organize, collect, transform and process large volumes of data from diverse sources, ensuring the maintenance and evolution of robust pipelines. • Data Visualization Culture: Lead the creation, modeling and presentation of metrics through analytical panels and intelligent dashboards using Amazon QuickSight, ensuring leadership makes decisions based on reliable data. • Security and Governance: Ensure control, integrity, quality and maximum security in access to the data handled. • Squad Collaboration: Actively participate in business refinement and technical development phases, working as part of a team within a continuous delivery culture.

• Own Marketing’s contribution to the Growth Marketing Reporting Framework • Partner with IT Data and Analytics and Sales Ops Analytics for integrated reporting • Identify performance trends and deliver findings to marketing leadership • Develop and maintain executive-ready dashboards in Salesforce • Execute contact database segmentation in Pardot • Establish and enforce data hygiene protocols

• Translate business needs into data requirements: work directly with business stakeholders to capture, clarify and prioritise analytical requirements, ensuring alignment between strategic goals and technical execution. • Own the full analytics delivery lifecycle: from scoping data needs and coordinating with data engineering, to building models, dashboards and reports in the relevant tooling, to presenting findings and insights to leadership. • Lead the OneView Dashboard initiative: consolidate KPIs from across the business (revenue, free subscriptions, campaign performance, web traffic, and more) into a unified, reliable reporting layer for one of our key SaaS brands. • Coordinate with data management and modelling teams to ensure timely delivery. • Drive the GTM Funnel Analytics programme: support the design and delivery of a centralised Go-To-Market funnel tracking system, covering lead acquisition, channel performance, and marketing automation across a portfolio of SaaS brands. • Expand analytics maturity over time: once GTM tracking is established for initial brands, extend the framework to include onboarding flows and product usage analytics, progressively enriching the analytical picture across the portfolio. • Act as a cross-functional enabler: proactively unblock dependencies across Data Platform, Analytics, BI, and Marketing automation Engineering — bringing the seniority and breadth of experience to contribute meaningfully across all these domains without hand-holding. • Collaborate with data tooling: work hands-on with the existing data stack (including Databricks, and BI/visualisation tools as required) and contribute to how data is modelled, structured and surfaced for business consumption.