Senior Director, Reporting & Analytics Engineering

About This Opportunity

We are representing a confidential global entertainment technology organization in their search for a Senior Director, Reporting & Analytics Engineering based in London. This is a transformational leadership role responsible for driving enterprise analytics capabilities from traditional reporting into a new generation of intelligent, AI-enabled, proactive analytics.

You will lead an organization of approximately 30 analytics engineers, report developers, visualization specialists, and people leaders focused on the last mile of the enterprise data supply chain: semantic models, curated data products, metric definitions, and consumption experiences that turn engineered data into business decisions.

This role requires both deep technical foundations in governance, dimensional modeling, and enterprise BI platforms, and a forward-looking mandate to build exception-based alerting systems, enable LLM-based data access, productize data science models, and design analytic agents that deliver insight proactively.

Responsibilities

Organizational Leadership

• Lead, coach, and develop a team of approximately 30 people, managing through frontline managers
• Own hiring, career pathing, performance management, and succession planning
• Define multi-year vision and roadmap for enterprise reporting and analytics engineering
• Manage organizational budget, vendor relationships, and contractor capacity
• Establish engineering culture within analytics: peer review, automated testing, documentation, source control, CI/CD

Analytics Engineering & Data Architecture

• Drive maturity of last-mile architecture: curated marts, semantic layers, reusable data products, certified datasets
• Define and enforce dimensional modeling standards and transformation frameworks
• Own the enterprise metric layer ensuring key business measures carry single, governed definitions
• Partner with Data Engineering on clear contracts between pipeline work and last-mile modeling
• Manage query performance, warehouse consumption, and platform cost as engineering concerns

Data Governance, Metadata & Lineage

• Own cataloging, business glossary, data certification, and stewardship workflows
• Maintain column-level lineage across analytics estate for impact analysis and change management
• Implement data access provisioning and entitlement models, including row and column-level security
• Drive data quality monitoring, freshness SLAs, observability, and incident response

Enterprise Reporting & Data Visualization

• Drive analytics engagement through enterprise visualization platforms in partnership with Data Engineering
• Set visualization and information design standards for readability, consistency, and accessibility
• Rationalize existing reporting portfolio: retire redundant assets, consolidate content, reduce technical debt
• Build durable self-service capability through training, templates, community support, and clear guardrails

Advanced, Proactive & AI-Enabled Analytics

• Partner with Data Science to productize models: build visualization, monitoring, and feedback loops
• Enable generative AI and LLM access to enterprise data with semantic foundations and governance
• Build exception-based analytics detecting statistically significant deviations using seasonality-aware baselines
• Route exceptions to accountable owners with context, drivers, and recommended actions
• Design analytic agents that proactively monitor data, investigate variances, and deliver insights
• Shift consumption model from pull to push: delivering right information to right person at right time

Cross-Functional Partnership & Prioritization

• Partner with Product Management on roadmap, requirements, user research, and release planning
• Run transparent intake, triage, sizing, and prioritization process with Analytics Operations
• Make capacity constraints visible and drive reuse over one-off builds
• Serve as executive-facing partner translating business questions into scoped analytic solutions

What We're Looking For

Required Qualifications:

• Bachelor's degree in Computer Science, Information Systems, Engineering, Statistics, Mathematics, Economics, or related quantitative field (or equivalent experience)
• 15+ years progressive experience in data, analytics, or business intelligence
• 8+ years leading teams and 4+ years managing managers
• Experience leading organizations of 25+ people in large, matrixed enterprises
• Strong hands-on foundation in SQL, dimensional modeling, and ELT/ETL design
• Production experience on modern cloud data warehouse or lakehouse (Snowflake, Databricks, BigQuery, Redshift, Synapse)
• Experience with transformation frameworks such as dbt
• Experience applying software engineering practices to analytics: Git workflows, automated testing, CI/CD
• Enterprise-scale experience with BI platforms (Domo, Tableau, Power BI, Looker) including governance and cost management
• Experience driving data governance covering catalog, lineage, glossary, stewardship, quality, and access
• Familiarity with governance platforms such as Atlan, Collibra, Alation, or Informatica
• Track record delivering jointly with Data Engineering and Product Management
• Direct experience partnering with Data Science, operationalizing and visualizing model output
• Working command of statistical concepts: hypothesis testing, confidence intervals, variance, seasonality, forecasting
• Experience running formal intake, prioritization, and capacity planning processes
• Excellent executive communication and influence skills
• Experience managing budget, vendor contracts, and platform licensing

Preferred Skills:

• Master's degree or MBA in related field
• Production experience with LLM-based analytics: retrieval-augmented generation, text-to-SQL, conversational BI
• Experience designing agentic workflows for monitoring, investigation, and notification
• Hands-on experience with Atlan, Domo, and Tableau specifically
• Proficiency in Python or R and familiarity with statistical/ML libraries and MLOps
• Experience deploying anomaly detection at scale including alert routing and fatigue management
• Familiarity with data product and data mesh operating models
• Experience with Agile or product operating models, portfolio and OKR management
• Experience leading global or matrixed teams including offshore delivery models
• Track record leading major platform migrations or rationalization efforts
• Success attracting, developing, and retaining senior technical talent

How We Work with You

Get A Job.ai is representing this confidential client in our capacity as their exclusive recruiting partner for this search. When you apply through our platform at getajob.ai, one of our experienced recruiters will review your background and conduct an initial screening conversation. If there's a strong mutual fit, we will prepare and submit your profile to our client for consideration.

Please apply only through Get A Job.ai. Do not attempt to contact the client organization directly, as we are managing this search on their behalf and direct contact may disqualify your candidacy.

Pay

Compensation details will be discussed during the screening process with our recruiting team and are dependent on experience and qualifications.

Equal Employment Opportunity

Get A Job.ai is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.