WHAT DOES A LEAD DATA ANALYST DO?
Published: Jan 12, 2026 - The Lead Data Analyst leads the design and deployment of advanced analytics across paid media and customer lifecycle marketing, enabling scalable and data-driven decision-making. This role defines and executes data strategy in partnership with marketing technology, data science, product, and engineering teams, including the implementation of multi-touch attribution and experimentation frameworks. The lead also delivers impactful reports, dashboards, and metrics while acting as a thought leader to influence strategy, optimize performance, and support the organization’s growth roadmap.
A Review of Professional Skills and Functions for Lead Data Analyst
1. Lead Data Analyst Duties
- Technical Leadership: Provide technical leadership to other analytics team members
- Solution Alignment: Link team-specific business requirements to best practice BI Analytics and Big Data solutions
- Problem Solving: Research and develop solutions to complex technical problems
- Stakeholder Partnership: Build strong partnerships with a broad range of business functions and identify where analytics solutions can add value
- Data Preparation: Conduct effective and efficient data preparation, transformation and visualisation
- Data Architecture: Maintain an understanding of the data architecture and relationships between various data sources
- Customer Engagement: Proactively engage with customers to understand, prioritise and communicate analytics needs that lead to improved business outcomes
- Data Governance: Drive participation in data governance architecture integration and change management alongside business stakeholders and domain experts
- Executive Communication: Present information effectively to all parts of ResMed up to the Executive level
- Technical Documentation: Document all activities and generate appropriate reports for internal and external use
2. Lead Data Analyst Details
- Strategic Analytics: Work closely with business leaders and other teams to plan and lead highly complex and business-impacting data analysis initiatives
- Requirements Discovery: Participate in discovery sessions to gather understanding and define business requirements
- Data Extraction: Extract data from a variety of sources including data lakes, databases and data models
- Trend Analysis: Identify, analyze and interpret trends or patterns in complex data sets
- Method Selection: Identify and apply appropriate analytical methods
- Method Explanation: Explain the benefits and limitations of analytical methods to stakeholders
- Data Storytelling: Present findings to stakeholders through engaging presentations, clear documentation and effective visualizations
- Data Recommendations: Provide recommendations and advice using proven data-driven analytics
3. Lead Data Analyst Responsibilities
- Request Prioritization: Prioritize analytics requests, communicate timeframes and manage request backlogs
- Data Transformation: Create processes through SQL and ETL to transform raw data into meaningful structured information
- Statistical Modeling: Create models that provide recommendations using statistical methods
- Dashboard Development: Create dashboard reports and visualizations that deliver clear business value and insights
- Requirements Discovery: Participate in discovery sessions to gather understanding and define business requirements
- Data Evangelism: Assist in furthering a data-driven culture by acting as a data analytics expert and sharing knowledge
- KPI Management: Identify, develop and monitor impactful KPIs
- Capability Planning: Identify missing data capabilities and plan approaches to address them
4. Lead Data Analyst Accountabilities
- Marketing Analytics: Lead design and deployment of analysis that spans paid media and customer lifecycle marketing efforts
- Data Strategy: Lead data strategy in partnership with Marketing Technology to build customer identity at Bestow
- Attribution Modeling: Lead design strategy implementation and migration of multi-touch attribution
- Experimentation Optimization: Assist in leading the optimization of experimentation and A/B testing processes and measurement
- Data Infrastructure: Create and optimize data infrastructure to scale and propagate data across teams and marketing stakeholders
- Thought Leadership: Act as a thought leader for data-informed initiatives and support the team's direction and roadmap
- Cross Functional: Partner with Data Science, Data Engineering and Product teams to solve problems at scale
- Strategic Influence: Inform influence and execute new strategies and tactics using analysis and impact metrics
- Reporting Enablement: Build reports, dashboards and metrics that enable the organization to scale successfully
5. Lead Data Analyst Functions
- Cyber Risk: Work with the market-leading cyber team to develop innovative risk scoring and accumulation tools to aid the understanding of underlying cyber risk
- Big Data: Key contributor to big data projects which underpin innovative analytics strategy for the Property business
- Data Quality: Focus on the augmentation of data quality and the development of a bespoke view of loss
- Relationship Management: Establish and maintain relationships with key brokers, clients and colleagues
- InsurTech Landscape: Understand the InsurTech landscape and how it could be used to benefit wider analytics objectives
- Marketing Performance: Develop new data requirements, maintain automated dashboards and analyze marketing performance
- Roadmap Management: Collaborate with business partners to manage intake roadmap prioritization and manage the team against key initiatives
- Trend Analysis: Identify, analyze and interpret trends in marketing data to identify opportunities and develop a strong understanding of current and potential marketing channels
- Funnel Analytics: Develop tools that articulate areas of opportunity across the marketing funnel and drive actionable insights
- Data Partnership: Partner closely with product and engineering teams to define the future of data for Supermetrics, with a focus on usability for marketing and sales
- Marketing Analytics: Design and deliver marketing analytics solutions around customer segmentation, attribution and lift studies to answer core marketing questions
- Data Collaboration: Work closely with other data teams across Supermetrics to ensure the ongoing evolution and improvement of data assets