• 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.

Role Description We are seeking a Sr. Data Analyst to support enterprise reporting, dashboard development, and applied data analysis for an evolving analytics project. This role will focus on Tableau reporting, SQL/Python analysis, data cleaning and preparation, and translating business questions into meaningful insights and outcomes. Enterprise experience strongly preferred. - Build, maintain, and support enterprise-level reporting and dashboards in Tableau. - Work with complex and sensitive datasets, including salary-related data. - Use SQL and Python to perform data analysis, analytical deep dives, and data preparation. - Take business questions and translate them into insights, conclusions, and actionable outcomes. - Own data cleaning responsibilities to ensure datasets are accurate, usable, and analysis-ready. - Apply foundational statistics to support analysis where needed. - Work within an evolving project environment with curiosity, flexibility, and a willingness to learn. - Collaborate with data engineering partners and understand data flow across systems, even though API automation will be handled by the Data Engineer. Qualifications - Strong applied data analysis experience using Python. - Python data cleaning experience. - SQL experience. - Tableau experience, including enterprise reporting and dashboard work. - Snowflake experience. - Ability to analyze business questions and produce meaningful insights. - Experience preparing, cleaning, and working with complex datasets. - Foundational understanding of statistics. Requirements - Experience working with HR data. - Experience working with sensitive data, such as salary or compensation data. - Understanding of data flow across systems. - Familiarity with BigQuery. - Exposure to AWS or similar cloud environments. Benefits - Remote role open to LATAM-based contractors. - US hours overlap required. - Full-time contract engagement. - Expected allocation is 40 hours per week. - Contract expected to run through March 31, 2027.