Analytics Lead Manager

Job Summary

The Data & Analytics function is dedicated to designing and delivering robust global data platforms that enable business solutions and high-quality analytics. The Analytics Lead (Manager) manages a team of analytics engineers accountable for delivering trusted, analytics-ready data products, semantic models, and self-service capabilities that turn enterprise data into actionable insight. This leader defines the analytics roadmap, drives adoption and enterprise data literacy, ensures governed and AI-ready data consumption, and partners with the Head of Data & Analytics and service line stakeholders to maximize the business value of data across the organization.

Responsibilities

• Strategy, Roadmap & Service Ownership
• Align the analytics roadmap with enterprise Data & Analytics strategy, business outcomes, and service line priorities, ensuring fit-for-purpose analytics products prioritized by measurable value and ROI.
• Define analytics service offerings (self-service reporting, curated datasets and semantic models, reusable analytics patterns, and tiered service levels).
• Insight Delivery, Quality & Governance
• Establish standards for analytics-ready (gold-layer) datasets, semantic models, and metric definitions to ensure consistent, trusted, and certified reporting.
• Sponsor data quality and observability for analytics outputs, including SLAs for data freshness and availability against consumer expectations.
• Ensure governance-by-design across analytics: standardized access, classification/metadata, end-to-end lineage, retention controls, and certified datasets.
• Partner with Data Governance, Privacy, and Data Owners/Stewards to ensure analytics outputs are accurate, compliant, and responsibly and ethically used.
• Analytics Engineering & Delivery Leadership
• Mature analytics engineering standards, reference patterns, and semantic models across the Medallion (Bronze/Silver/Gold) architecture, leveraging dbt for transformation and Power BI for delivery.
• Drive analytics automation and productivity: CI/CD for analytics assets, semantic-layer reuse, and AI-ready data preparation (including Snowflake Cortex AI enablement).
• Provide executive-level stakeholder management for analytics delivery commitments, intake and prioritization, and escalations.
• Leadership & Talent
• Build and lead a high-performing team of analytics engineers.
• Define operating model, roles, sourcing strategy (including global delivery centers), and technical and analytics career paths.
• Set measurable goals for adoption, data quality, delivery velocity, cost, and user satisfaction.
  
  
  

Skills

Skills and Experience

• English level B2+
• 10+ years of relevant experience with demonstrated leadership in analytics delivery, analytics engineering, and BI/insight products; 3+ years in leadership or team-lead roles.
• Proven ability to deliver enterprise-grade analytics and self-service capabilities with strong governance and data quality alignment.
• Strong technical breadth across analytics engineering, semantic modeling, BI and visualization (Power BI), cloud data platforms, and modern transformation tooling (dbt).
• Executive communication, storytelling-with-data, and presentation skills.
• Experience building analytics-ready data products and semantic layers at scale (including data quality and observability) and driving adoption and data literacy.
• Experience with Agile delivery, intake and prioritization practices, and Snowflake/Informatica IDMC platform best practices.
• Proven experience with Machine Learning, predictive analytics, and natural language processing.
• Strong programming skills in SQL and Python for data validation, profiling, reconciliation, and analytics.
• Experience with data modeling methodologies (Dimensional modeling, Data Marts, Data Warehousing, Star/Snowflake schema).
  
  
  

Education / Professional Experience/ Qualifications

• Bachelor’s degree in information technology, Computer Science, Engineering, Analytics, or related discipline.
• Snowflake experience is required.
• Hands-on experience with BI and analytics engineering tools (e.g., Power BI and dbt) is required.
• Preferred: Experience in professional services, accounting industry, or client service/consultative technology roles.