Position Description: Data and Reporting Analyst

Location: Sydney — hybrid, 2-3 days on-site at WeWork

Type: Permanent. Full-time preferred; four days per week considered

Reports to: Client Success Manager

Ideal background: A degree in data science, statistics, computer science,

mathematics or engineering

Level: Early career, on a deliberately technical development track

About the Role

We work with household-name Australian charities — organisations most people have donated to, volunteered for, or grown up knowing. Our job is to help them understand their supporters properly so they can raise more money and do more good with it.

At the centre of that work is Ignte, our data hub. Ignte holds de-identified data on 25

million supporters, which lets us show a charity not only how their own fundraising is performing but how it compares with the sector. Fundraising teams use it to raise more money and to build genuinely better supporter experiences.

This is the technical role behind that platform. You will start by making sure client data is right and building the reports that carry our analysis to clients. From there we will train you deliberately and steadily on the technical stack: SQL, our data preparation workflows, dashboard development in Tableau, and statistical modelling in R or

Python.

The first few months involve careful, detailed data work so you’ll definitely want to love data. This will help you learn about the data we process and our tech stack. We will invest seriously in your technical skills, and by the end of your first year you will be doing work that most analysts at your stage do not get near — developing dashboards, running the pipelines that a national charity depends on, and starting to build statistical models.

You will work closely with our Director, Senior Consultant, Client Success Manager and data scientist throughout. This is a small team, so you will see the whole business and your work will reach real clients quickly. Nothing you produce goes out unchecked, but plenty of it goes out.Key Responsibilities

- Data Quality and Assurance
- Review incoming client data files and assess whether they look complete and correct before anything else happens
- Reconcile what has loaded into the hub against what the client provided, and confirm the numbers hold up
- Investigate discrepancies through to root cause — misaligned identifiers,

incorrect categories, missing fields, unexpected movements — and see them resolved

- Write and run queries to check data yourself rather than waiting to be told what is wrong
- Keep documentation, trackers and definitions current so the team can rely on them

2.

Client

Reporting

- Build client reports from our dashboards, following our established process
- Draft the interpretation and commentary that goes with the numbers, using our

AI-assisted process, and check it carefully. The draft is assisted; the accuracy is yours

- Prepare charts, tables and supporting material for client workshops and meetings
- Help respond to client questions about their data, with support
- Data Pipelines and Processing — From Around Three Months
- Learn and run our automated data preparation workflows to process and load client data
- Take on routine processing independently, then progressively more complex ingestions
- Help improve and document the process so it becomes faster and less manual over time
- Understand our data model well enough to know where a number comes from and why

4.

Dashboard





Development — From Around Six Months• Amend existing Tableau workbooks — adjusting calculations, correcting groupings, adding filters

- Progress to building new views and dashboards, and publishing them for client use
- Choose chart types, layout and hierarchy that make the finding obvious —

designing for how a fundraising team will actually read the dashboard, not for what is easiest to build

- Manage data sources, refresh schedules and permissions
- Keep definitions consistent so a metric means the same thing wherever it appears
- Manage the release cycle for dashboard changes — moving work from development through testing to production, tracking what changed, and publishing to clients on a predictable schedule

5.

Statistical

Modelling — From Around Nine Months

- Build capability in R or Python for applied statistical work, with structured training and support
- Contribute to propensity scoring, segmentation and value modelling across the supporter base
- Apply significance testing to research and campaign results, and understand what they do and do not support
- Take a model from exploration through to something reliable enough to put in front of a client

What We’re Looking For

We are hiring for technical aptitude, analytical judgement and ambition rather than for a list of tools. You do not need production experience in any of our stack. You do need to be the kind of person who takes a system apart to understand it.

Essential

- A bachelor’s degree in data science, statistics, computer science, mathematics,

engineering, econometrics or a similar quantitative discipline• Some hands-on exposure to R or Python — coursework, a university project or self-taught work is all fine, provided you have actually written code and can talk about it

- A sound grasp of statistical concepts: significance, sample size, distributions,

correlation and its limits

- Some exposure to SQL, or transparent evidence you will pick it up quickly
- Strong technical aptitude — you learn new software fast, enjoy working out how a tool actually functions, and will read documentation rather than guess
- An aptitude for interpretation — you can look at a result and work out what it means and what it does not mean, rather than simply reporting what it says
- Real attention to detail. You check your work, and you would rather find the mistake yourself
- Clear written English — you can explain a technical finding in a way a non-

technical reader will follow

- An appreciation that valuable design improves comprehension. A correct chart that is hard to read has failed, and you care about the difference between the two
- A reliable ambition to become technically excellent, and the discipline to keep at it through the unglamorous parts
- A genuine desire to do work that matters. Our clients are charities, and the point of the analysis is to help them do more positive
- Organised, and able to keep several pieces of work moving at once
- Eligibility to work in Australia. This position is not eligible for visa sponsorship

Desirable

- Any exposure to Tableau, Power BI or similar dashboard tools




- Any exposure to a visual data preparation tool such as KNIME, Alteryx or Power

Query

- Any exposure to PostgreSQL or another relational database
- Any exposure to statistical modelling — regression, classification, clustering —

including through coursework

- A personal project, competition entry or portfolio you can walk us through
- Prior experience of or volunteering in the charity and not-for-profit sectorYour First Twelve Months

Months one to three

- You understand our data model, our clients and our reporting process
- You are checking incoming client data confidently and spotting problems before anyone else does
- You are writing your own queries to validate numbers
- You have documented the data structure and the calculation logic behind our dashboards — where each metric comes from, how it is derived, and where it is used

Months three to six

- You are running routine data processing independently
- You own reporting for several clients, with light review
- You are making straightforward dashboard amendments confidently

Months six to twelve

- You are handling complex ingestions and building new dashboard views
- You have begun contributing to propensity and segmentation models in R or

Python

- You are the person the team asks when a number needs explaining

Where This Role Can Lead

We are deliberately hiring below the level of the role we expect this to become. As you build capability, the scope of the position is intended to grow with you, and we will actively shape it around your strengths.

Depending on where your interests take you, the pathways from here include:

- Senior Analyst, owning analysis and reporting end to end across a portfolio of charities
- A data science direction — propensity modelling, segmentation, value forecasting and the analytical products built on top of the hub
- A data engineering and platform direction — pipelines, data modelling and the technical backbone of Ignte
- A consulting and insights direction, if client-facing work turns out to be where your strengths lie• Responsibility for others as the team grows

Why This Role Matters

Charities operate under real constraint. Every dollar spent reaching the wrong supporter is a dollar not spent on the cause, and most charities do not have the internal capability to work out the difference. That is the gap we exist to fill, and Ignte is how we do it at scale.

A platform is only as good as the data inside it and the rigour applied to it. This role holds both. The organisations relying on your work are names the whole country recognises, and the decisions they make on the back of it affect real people.

You will be joining a small, motivated team that will invest in you properly — with structured training, direct mentoring from senior practitioners, and real responsibility as soon as you are ready for it.

If you want to become genuinely good at this, and you want the work to add up to something, this is a good place to start. We are looking for someone who wants to grow with us, not pass through.

How to Apply

Please send your CV together with a short application telling us about something technical you have taught yourself, and how you went about it. Please email to [email protected].

Shortlisted candidates will complete a short practical exercise reviewing a dashboard and asked to explain the insights.

We know that not every candidate will tick every single box — but if you are excited about this role, eager to learn, and aligned with our mission, we would love to hear from you.

📌 Data and Reporting Analyst (Sydney)
🏢 Ignte
📍 Sydney