Data Analytics Manager

We are looking for a leader to run the analytics function, the team, platforms, and practices that turn data into decisions. The role helps the organization decide what to measure, where trustworthy data lives, and how findings should influence action, overseeing dashboards, recurring performance reporting, ad hoc investigations, experiments, forecasting inputs, and self-service reporting. They lead analysts and data professionals and are the link between raw data and the actionable insight that drives strategic decisions.

Modern analytics-leadership briefs now fuse data, AI, and platforms, integrating sources into a governed ecosystem with high standards of data quality, lineage, governance, and privacy compliance, and increasingly sit at the hub of analytics tool rationalization and governance coordination.

We are seeking an analytics leader focused on business outcomes who translates complex data into understandable reports and recommendations, and who holds a high bar for data quality, accuracy, and reliability. They develop analytics talent and foster a culture of data-driven decision-making across departments.

This is a senior-management profile that partners across analysts, data scientists, data engineers, and business stakeholders. It suits someone open to a hybrid or remote-first engagement, and to mobilization to the Middle East, Europe, or North America depending on the client. The person we want makes analytics genuinely useful and trustworthy.

A strong candidate for this role has run an analytics function and delivered insight that changed decisions, someone who has owned data quality and governance, rationalized tools, and developed analysts. They bring an openness to accelerating analytics with governed AI.

In practice, the responsibilities break down as follows:

• Analytics leadership: Own the analytics roadmap and delivery of decision-grade insights; decide what to measure and how findings influence action; manage and develop a team of analysts and data professionals.
• Data quality & governance: Ensure data quality, lineage, definitions, and governance; coordinate governance and analytics tool rationalization.
• Stakeholder value: Partner with the business to prioritize and deliver high-value analytics and self-service reporting.
• AI-accelerated analytics: Operationalize agentic assistants and governed foundation models to accelerate insight, with trust, privacy, and governance intact.

We want to see an analytics leader fluent in BI and data who insists on trustworthy data and decision-grade output, and who is bringing governed AI into analytics thoughtfully rather than chasing hype.

Core analytics

• BI / analytics platforms, SQL, data modeling, visualization, experimentation/forecasting.
• Analytics governance, metric definitions, data quality, lineage.
• Team and stakeholder management.

Analytics performance (KPIs from research)

• Steers insight adoption, data quality/accuracy, self-service coverage, reporting timeliness, and decision impact, with governance and lineage as first-class measures.

Modern Agentic AI / AIOps (niche areas we are seeking, depth explored at interview)

• Assistants that generate analysis and draft reports, with human review.
• Governed foundation-model use (Amazon Bedrock or equivalent) for analytics acceleration, respecting data privacy.
• Monitoring analytics pipelines and data-quality anomalies.

These niche AI areas are seeds we are looking for; depth will be explored during the interview process.

This role is delivered through Solutions Chapter Group's Human Resources chapter (Chapter 12) as a Recruitment Process Outsourcing (RPO) engagement, under our Technical Recruitment stream. We use a curated professional recruitment model: candidate profiles are pre-vetted in our internal database, and when a required profile isn't already available, our dedicated Scout network conducts global headhunting to secure it. We screen and match candidates against each client's specific requirements, and placements may be remote or an on-site deployment with mobilization to the Middle East, Europe, or the United States.

From a recruitment-fit perspective, we screen for:

• A business-outcome focus that translates data to decisions.
• Strong stakeholder communication.
• A data-quality, lineage, and trust mindset.
• The ability to develop analytics talent.
• Openness to the engagement model (remote or mobilized on-site) and readiness for cross-region deployment.

Areas to explore at interview *(topics only)*

• An analytics program that changed a decision
• Ensuring trustworthy data (quality, lineage)