Analytics Lead, Data Analytics & Modeling

Hands‑On Technical Leadership

• Design, build, and maintain scalable data models, datasets, and analytical solutions with a focus on correctness, performance, and reusability.

• Write, review, and own production‑quality SQL and Python code across data pipelines, transformations, and analytical workflows.

• Serve as a technical lead on complex projects—defining approach, driving design decisions, and ensuring high‑quality execution.

• Partner closely with data engineering and platform teams to influence data architecture, modeling standards, and tooling.

• Ensure analytics solutions are built on trusted, well‑governed, and sustainable data foundations.

Analytics & Solution Delivery

• Lead the delivery of high‑impact dashboards, metrics, and analytical products that support strategic and operational decision‑making.

• Translate ambiguous business problems into structured analytical approaches, data models, and technical solutions.

• Apply advanced analytical techniques (e.g., statistical analysis, predictive modeling, machine learning where appropriate) to identify trends, risks, and opportunities.

• Drive automation and standardization of reporting and analytics workflows to improve scalability and reduce manual effort.

• Own outcomes for key deliverables, ensuring timelines, quality, and business impact are met.

Project Leadership & Mentorship

• Lead analytics workstreams across multiple concurrent initiatives, coordinating across stakeholders and ensuring alignment to business priorities.

• Mentor and support junior analysts through code reviews, design discussions, and hands‑on coaching.

• Promote best practices in data modeling, coding standards, and analytical rigor across the team.

• Act as a bridge between business stakeholders and technical teams, ensuring solutions are both business‑relevant and technically sound.

• Contribute to shaping analytics priorities and roadmaps, balancing near‑term delivery with long‑term data quality and scalability.

Qualifications:

• 4+ years of experience in data analytics, data engineering, or related technical roles with strong hands‑on delivery.

• Proven experience leading complex analytics or data initiatives as an individual contributor.

• Strong experience designing scalable data models (e.g., dimensional, semantic, or analytical models).

• Advanced proficiency in SQL and Python, with experience maintaining complex analytical codebases.

• Experience partnering closely with data engineering teams on data pipelines, architecture, and data platforms.

• Deep understanding of analytics and BI concepts, with experience using tools such as Power BI, Tableau, Looker, or similar.

• Strong ability to translate ambiguous business problems into well‑structured technical solutions.

• Excellent communication skills, with the ability to clearly explain technical concepts to both technical and non‑technical audiences.

Preferred Experience:

• Experience mentoring analysts in a technical lead or informal leadership capacity.

• Familiarity with modern data platforms (e.g., cloud data warehouses, transformation frameworks, orchestration tools).

• Experience operating in complex, enterprise or regulated environments.

• Background in financial services, wealth management, or advisor‑focused businesses.

Special Factors

Sponsorship

About Vanguard

At Vanguard, we don't just have a mission—we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.