This person makes sales data reliable and useful across our programs. They design how data is captured, structured, calculated and reported in each client environment, build it themselves, and turn it into better decisions, better leads and fewer leaks in the funnel.

This is not a data science role and not a pure dashboard role. It requires the discipline of a data engineer (structure, documentation, quality checks) applied with practical tools: Salesforce, Google Sheets, Apps Script, SQL where available, and BI tools.

The role works at four levels:

Builder: designs and builds the data and reporting setup of each program, personally, with the tools the client allows. Technical advisor to clients: explains what the current access allows, what it does not, and which additional access or tools would solve a specific business problem. Team lead: leads the team of 4 Data Analysts, sets priorities, raises their technical level and sets common standards and templates across programs. GTM engineer (growing scope): builds tools that generate pipeline and optimise sales processes, on top of the data foundations.

Requirements

Data foundations in client environments

Map, for each program, which data is available, where it lives, how often it refreshes and what access we have. Design and build a reliable setup within those limits: Salesforce reports and report types, scheduled exports, structured Google Sheets, Apps Script automations, BigQuery or SQL where granted. Keep history where the client systems do not, through regular snapshots, so that trends and comparisons are always possible. Apply engineering discipline: separate raw data from calculated data, document every definition, build checks that flag missing or wrong data before it reaches a report. Reconcile our numbers with client and finance figures, and resolve differences quickly and transparently.

Metrics and reporting

Define one common metric dictionary across programs (pipeline, conversion, revenue per rep, attainment), while respecting each client's own KPIs and contracts. Replace manual reporting with automated, reliable flows in Looker Studio, Tableau, Salesforce dashboards or Sheets. Make sure the inputs for weekly reviews, monthly client packs and quarterly incentive calculations come from the same trusted source.

Client advisory and access

Lead technical conversations with client stakeholders on data access and tools, and build the business case for any additional access (for example a read-only API, a scheduled export or a dataset). Handle difficult conversations: unreliable client systems, delayed data, conflicting numbers, requests the current setup cannot support. Respect client data ownership, security rules and GDPR in every solution.

Sales process analysis

Analyse funnels with operations leaders to find where pipeline and revenue leak, and support process changes with data. Measure lead quality end to end, from list to meeting to closed won. Package what works into reusable templates and playbooks. What travels between programs is the method, never client data.

Team leadership and stakeholders

Lead the team of 4 Data Analysts: set priorities, review their work, develop their technical skills, and set shared standards and templates. Work directly with the Director of B2B Sales Programs and with the Heads of Operations, as the data partner of the operations leadership. Work with client sales leaders, TP operations teams, finance and IT. Balance competing requests across programs, set priorities and deliver fast with limited resources.

Additional layer: GTM engineering

Beyond data and reporting, this role will be responsible for building tools that generate pipeline and make our sales processes faster and more effective. Prior GTM engineering experience is not a requirement: we expect the right candidate to grow into this part of the job, with our support. Interest and curiosity for this area are essential.

In practice, this layer includes:

Building lead generation tools:

📌 Revenue Analytics Lead (Barcelona)
🏢 Teleperformance
📍 Barcelona