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
Editorial Process
Lamwork content is developed through structured review of publicly available job postings and documented hiring trends.
Editorial operations are managed by Thanh Huyen, Managing Editor, with research direction and final oversight by Lam Nguyen, Founder & Editorial Lead. Content is periodically reviewed to reflect observable labor market changes.