Analytics Lead Manager

Description

Summary: The Analytics Lead manages a team of analytics engineers to deliver trusted, analytics-ready data products and drive adoption of data platforms for business insights. Highlights: 1. Lead a high-performing team of analytics engineers 2. Define analytics roadmap and drive data literacy 3. Deliver enterprise-grade analytics and self-service capabilities 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 o 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. o Define analytics service offerings (self\-service reporting, curated datasets and semantic models, reusable analytics patterns, and tiered service levels). * Insight Delivery, Quality \& Governance o Establish standards for analytics\-ready (gold\-layer) datasets, semantic models, and metric definitions to ensure consistent, trusted, and certified reporting. o Sponsor data quality and observability for analytics outputs, including SLAs for data freshness and availability against consumer expectations. o Ensure governance\-by\-design across analytics: standardized access, classification/metadata, end\-to\-end lineage, retention controls, and certified datasets. o 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 o 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. o Drive analytics automation and productivity: CI/CD for analytics assets, semantic\-layer reuse, and AI\-ready data preparation (including Snowflake Cortex AI enablement). o Provide executive\-level stakeholder management for analytics delivery commitments, intake and prioritization, and escalations. * Leadership \& Talent o Build and lead a high\-performing team of analytics engineers. o Define operating model, roles, sourcing strategy (including global delivery centers), and technical and analytics career paths. o Set measurable goals for adoption, data quality, delivery velocity, cost, and user satisfaction. Skills and Experience: Skills* 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.