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Findasense

Global CX consultancy delivering data-driven experiences

Global Head of Data Intelligence - Analytics, IA

Engineering LeadershipPosted on Nov 13
Full-timeMadrid, Spain

About the Job

Requirements

  • At least 7 years of experience leading data analytics or AI teams in global or multicountry contexts, with a track record of large-scale transformation programs.
  • Experience defining methodologies, governance, and service standards such as KPIs and SLAs.
  • Proven ability to lead multidisciplinary teams across data science, data engineering, business intelligence, research, and marketing technology, and align multiple stakeholders.
  • Knowledge of social listening platforms including Sprinklr, YouScan, Brandwatch, and Sprout Social, and social media analytics.
  • Knowledge of digital and social media campaign metrics and performance marketing.
  • Understanding of Salesforce Marketing Cloud and the customer relationship management ecosystem, including journeys, audiences, and activation.
  • Experience administering SQL and NoSQL databases, designing data models, and managing data quality.
  • Knowledge of social web application programming interfaces and advertising and analytics connectors.
  • Knowledge of end-to-end tools such as Domo or equivalent tools.
  • Knowledge of AI solutions including Gemini, GPT-5, Perplexity, and Claude.
  • Ability to combine and enrich information from social, customer relationship management, web/app, e-commerce, sales, brand-tracking, and call-center sources.
  • Advanced English for presentations and workshops with global audiences.

Responsibilities

  • Lead and scale a global team across data science, data engineering, and analytics in multiple time zones, focusing on operational excellence, collaboration, and value delivery.
  • Define the intelligence and analytics roadmap, including use cases, backlog, priorities, and objectives and key results, in alignment with business strategy and market needs.
  • Orchestrate the end-to-end portfolio from ideation, scoping, design, development, deployment, and adoption through minimum viable product and scaling; remove blockers and ensure on-time, on-quality, and on-budget delivery.
  • Establish standards and governance supported by the data engineering team, including methodologies, data contracts, data quality and lineage, security and privacy, machine-learning operations and large-language-model operations, and experimentation such as A/B testing and causal analysis.
  • Oversee data engineering, including data model and batch/streaming pipeline design, integration of social, customer relationship management, web/app, e-commerce, and sales sources, reliability, and cloud costs.
  • Build and evolve descriptive, predictive, and prescriptive data models and analytics for personalization, campaign optimization, and forecasting.
  • Drive multichannel marketing analytics across paid, owned, and earned channels and customer relationship management; advanced social listening; and automated executive dashboards.
  • Manage talent through hiring, onboarding, career paths, performance reviews, mentoring, and continuous upskilling, while fostering a learning and high-performance culture.
  • Plan capacity and budgets, allocate resources, negotiate with partners and vendors, and optimize x-as-a-service costs.
  • Align C-level, market, product, IT/security, and marketing stakeholders on service agreements such as KPIs and SLAs, value-based prioritization, and market adoption.
  • Communicate impact through executive storytelling, value measurement, and scalable success cases.
  • Ensure responsible AI, ethics, transparency, and regulatory compliance across developments and activations.
  • Develop accelerators such as dashboards, pipelines, and AI agents to automate processes and enable data extraction, analysis, and activation at scale.

Desired Qualifications

  • Programming in Python and/or R, ideally both; building API/ETL/ELT pipelines; orchestration with Airflow or Prefect; and version control with Git.
  • Knowledge of social web application programming interfaces and advertising and analytics connectors.
  • Cloud solutions including AWS, Google Cloud Platform, and Microsoft Azure, including data lakes/warehouses, functions, and orchestration.
  • Visualization using Tableau, Power BI, and/or D3.js, and executive dashboard design.
  • Causal modeling, experimental design, and impact evaluation.
  • Structured thinking and synthesis of complex information, with an orientation toward impact and business value.
  • Executive storytelling and clear communication with technical and non-technical audiences.
  • Leadership, proactivity, and a focus on continuous improvement and efficiency.

About the Company

Findasense

Global CX consultancy delivering data-driven experiences

Findasense helps brands improve how they interact with people by offering consulting, agency services, and technology integration to create smooth customer journeys across phone, social, web, mobile, retail, and other channels. Its products and solutions use data science to tailor experiences and content to each user, coordinating across channels to move customers toward desired actions. What sets Findasense apart is its combination of strategy, creative execution, and tech implementation, plus deep knowledge of consumer behavior across more than 10 industries and a global footprint with local expertise in about 20 countries. The company works with major brands to drive digital transformation and to connect with people in meaningful ways, aiming to make business a positive force for change.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
Madrid, Spain
Founded
2007

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