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Location
Remote (LATAM)
Seniority
Architect · 8+ years exp
Employment
Full-Time

First seen by Alion on Nov 1, 2026.

Overview
Company
Impact
Profile match
B2B marketing agency for technology and healthcare brands. Strategy, brand, demand generation, content, and HubSpot implementation.

About RAB2B

  • RAB2B is a global B2B marketing agency that partners with ambitious brands to drive measurable growth. We combine strategic thinking, media excellence, and operational rigor to deliver integrated solutions across markets. Our culture is built on accountability, clarity, and performance — empowering our teams to lead with ownership while collaborating across disciplines.

About the role

RAB2B is growing its data practice into a service clients buy in its own right. The Data Director sets its direction and leads the team that delivers it.

The role owns how data creates commercial value across the agency: the strategy, the capability roadmap, the offerings taken to market, and the narrative that persuades a client to invest. The Data Director partners with media, account and performance leadership as the person accountable for what data makes possible, and sits with client marketing leaders as the person who explains what their investment produced and what it should fund next.

The practice serves enterprise B2B clients across technology, manufacturing and healthcare, delivering measurement, reporting and dashboarding on a modern cloud data stack. Its next phase centers on advanced attribution and incrementality, marketing mix modeling, AI-assisted measurement and a portfolio of commercial data offerings.

This is a builder’s mandate. The Data Director carries end-to-end authority over the data discipline — strategy, capability, commercial offerings and team design — with the latitude to set the practice’s direction and the accountability that comes with it.

What you'll do

1. Commercial leadership of data
  • Define the commercial strategy for data at RAB2B: what we sell, to whom, at what price and with what proof.
  • Develop monetizable data products and services that grow client accounts and create agency revenue. Shape and price them jointly with media, account and finance leadership, against a shared target for what they produce.
  • Partner with business and client leads to identify high-value data use cases across existing accounts and new logos, then deliver them.
  • Present investment recommendations (data sources, partners, platforms, licenses) to the executive team, with the business case behind each one.
2. Data strategy and capability
  • Build the capability roadmap and align the organization behind it: the methods, the stack, the sequence and the investment each stage requires.
  • Lead the move past campaign reporting into multi-touch attribution, incrementality testing and marketing mix modeling, including a clear view of where each method holds and where it breaks.
  • Build on the team’s early adoption of AI-assisted measurement: decide where AI belongs across the practice, scale what already works and set the standard for the discipline.
  • Identify the data sources and partners worth acquiring, and negotiate the terms.
3. Client-facing leadership
  • Embed data across the commercial cycle: pitches, RFP responses, strategic planning, media activation and effectiveness measurement.
  • Translate complex data into actionable insight and a commercial narrative that moves a CMO to act.
  • Own the measurement conversation in the room: model the path from media investment to pipeline, qualified opportunity and closed revenue, and defend that model under scrutiny.
  • Raise client ambition through insight, storytelling and thought leadership.
4. Standards, team and organization
  • Own the standards by which the practice operates — measurement frameworks, taxonomy, data governance and reporting quality — and hold the discipline to them.
  • Build and lead a cross-functional team of data strategists, analysts and technologists, and define the shape that team takes as the practice scales.
  • Partner with the MarTech and Digital Experience teams, who own tagging, consent, CRM and marketing automation, so the data the practice reads and sells is trustworthy.
  • Make the case for data internally and build agency-wide fluency in what the practice offers.

Qualifications

  • 8+ years in data strategy, analytics or data-driven marketing, with progressive leadership responsibility across teams and client relationships.
  • A track record of building or scaling a data capability inside an agency, holding company or consultancy.
  • Commercial fluency: experience shaping offerings, defending pricing and contributing to revenue, not only to delivery.
  • Depth across paid media measurement (search, social, programmatic, partner media) and web analytics.
  • Hands-on experience designing and defending advanced measurement — multi-touch attribution, incrementality testing and marketing mix modeling — and a clear rationale for choosing one method over another.
  • Command of the modern data stack: SQL, a cloud warehouse (BigQuery preferred) and visualization tools such as Looker Studio, Tableau or Power BI.
  • Executive presence: able to hold a room of client executives, answer hard questions under pressure and influence decisions.
  • Fluent professional English: US client leadership, RFP defense and agency-wide written communication.
  • Daily use of AI in their own work, and a considered view of where it belongs in an analytics practice.
  • Remote, based in LATAM. Works on US client hours. Able to travel to the United States as needed.

    Preferred
  • Experience inside a holding-company data, analytics or product group (Publicis, Omnicom, IPG, WPP, dentsu), and the perspective that comes from operating at scale.
  • B2B experience, where cycles run long and revenue attribution runs through a CRM; technology, manufacturing or healthcare especially.
  • Marketing mix modeling built hands-on with open-source tools (Robyn, Meridian) or commissioned from a platform partner.
  • Experience productizing analytics: scoping, pricing and staffing measurement engagements as a commercial offer.
  • Familiarity with regulated categories (healthcare, pharma, financial services) and the compliance constraints they carry.
  • Spanish fluency.
  • Python for analysis and automation; CDP or CRM data work in Salesforce or HubSpot; syndicated research such as MRI Simmons, Comscore or TGI.

Originally posted on Himalayas

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