Analytics & USL Lead

The role acts as the senior technical authority for analytics delivery, partnering with Product Managers, Business Analysts, Architects, and Platform teams, while managing and developing Tech Leads and senior engineers. 

The Analytics & USL Lead within the Analytics CoE. 

This role ensures that analytics solutions delivered across the portfolio are: 

• →Technically consistent and scalable 

• →Aligned to enterprise architecture and standards 

• →Delivered predictably with high quality 

• →Built and sustained by high‑performing teams 

The role acts as the senior technical authority for analytics delivery, partnering with Product Managers, Business Analysts, Architects, and Platform teams, while managing and developing Tech Leads and senior engineers. 

Role Responsibilities: 

Portfolio‑Level Technical Strategy & Architecture 

• →Own and evolve the technical strategy for analytics across multiple pods/products 

• →Define and govern enterprise‑level analytics architecture, including:  

• →Data ingestion and integration patterns 

• →Data modeling and semantic layer standards 

• →Reporting and analytics consumption patterns 

• →Drive standardization, reuse, and simplification to reduce technical debt 

• →Review and approve technical designs for major initiatives and cross‑pod solutions 

Program / Portfolio Delivery Governance 

• →Provide technical oversight across multiple analytics pods 

• →Ensure consistent application of:  

• →Design standards 

• →Coding and modelling best practices 

• →Data quality and validation frameworks 

• →Own technical risk management at portfolio level (dependencies, scalability, performance) 

• →Act as final technical escalation point for complex delivery issues 

Partnership with Product, BA & Architecture Leadership 

• →Partner with Product Managers to align portfolio roadmaps with technical feasibility 

• →Work with Senior BAs to ensure KPI frameworks and metric logic are technically sound and scalable 

• →Collaborate with Solution / Enterprise Architects to ensure alignment with:  

• →Platform strategy 

• →Security, compliance, and governance standards 

• →Influence prioritization decisions by articulating technical trade‑offs and impacts 

Hands‑On Technical Leadership (Selective, High‑Impact) 

• →Step in hands‑on for:  

• →Complex architecture decisions 

• →Large migrations / rationalization efforts 

• →Cross‑domain analytics solutions 

• →Guide teams on:  

• →SAP BW / HANA / S/4 data models 

• →Data warehousing, Lakehouse, DataLake, ETL / ELT patterns 

• →Cloud analytics platforms (AWS, Snowflake, etc.) 

• →Ensure analytics platforms are future‑ready, not just fit for current use cases 

Analytics Technical Solution Ownership 

• →Own the end‑to‑end technical design of analytics solutions within assigned pods or products 

• →Define future‑state analytics architecture, including data flows, integration patterns, and semantic layers 

• →Review and approve data models, pipelines, and reporting architectures 

• →Ensure solutions are scalable, performant, reusable, and maintainable 

Team Leadership & Mentorship :  

Leadership of Tech Leads & Senior Engineers 

• →Line‑manage and mentor Tech Leads and senior analytics engineers 

• →Set clear expectations for:  

• →Technical ownership 

• →Delivery accountability 

• →Quality standards 

• →Coach Tech Leads on:  

• →Decision‑making 

• →Stakeholder communication 

• →Balancing speed vs sustainability 

Talent Development & Capability Building 

• →Build a strong analytics engineering leadership bench 

• →Define and drive skill development paths for:  

• →Data engineering 

• →BI & semantic modeling 

• →Cloud and platform capabilities 

• →Identify skill gaps and partner with CoE leadership on:  

• →Hiring strategy 

• →Upskilling plans 

• →Vendor augmentation where required 

Culture, Ways of Working & Engineering Excellence 

• →Champion product‑based delivery and engineering discipline 

• →Promote strong collaboration across Product, BA, Engineering, and Platform teams 

• →Embed a culture of:  

• →Ownership 

• →Reuse over reinvention 

• →Data quality and reliability 

• →Act as a role model for technical and people leadership 

Minimum Requirements: 

Functional & Domain Experience 

• →14–16+ years in analytics, data engineering, or BI  

• →Proven experience leading large‑scale analytics programs or portfolios 

• →Strong domain exposure in Supply Chain, Manufacturing, Retail, Sales, Finance, or Operations 

• →Experience delivering enterprise‑scale analytics solutions 

Technical Skills 

• →Strong hands‑on experience with: ETL / ELT Cloud platforms (AWS, Snowflake preferred), Databricks, Open Source, SAP Analytics (BW, HANA, S/4) Data Warehousing and  

• →Strong grasp of:  

• →Data modeling and semantic layers 

• →Analytics performance and scalability 

• →Integration patterns across heterogeneous source systems 

• →Experience with BI platforms (Power BI, Looker, Tableau, Qlik, etc.) 

• →Support complex data analysis, troubleshooting, and solution rationalization 

• →Guide teams in modern analytics and data engineering practices 

Soft Skills 

• →Proven people management experience with senior technical staff  

• →Strong influencing skills across business and technology leadership  

• →Ability to communicate complex technical concepts in business terms  

• →High ownership mindset with enterprise‑level thinking  

• →Comfortable operating in ambiguity and driving clarity at scale 

• →Excellent communication and stakeholder management skills 

• →Ability to influence without authority 

• →Strong coaching, mentoring, and feedback skills 

• →Ability to influence and motivate teams without micromanagement 

• →Strong communication and conflict‑resolution skills