IT & Development ✦ Dedicated & full-time

Data
Analyst

Dashboards, SQL and reporting that turn your data into decisions — from $14/hr + GST.

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$14/hrFrom, + GST · full-time
70%Average saving vs a local hire
14 daysBrief → first day
Fully managedWe hire, you lead

What a Data Analyst does

A data analyst makes your numbers useful — building dashboards, writing SQL and producing reporting that leaders act on.

Every StaffingSolutions.io data analyst is recruited, hired and managed by us — reference-checked for your tools, working your business hours, and backed by our zero-risk promise: no placement fee, money-back first week, and a free replacement if the fit isn't right.

What they handle

  • Dashboards — Power BI, Looker, Tableau.
  • SQL — queries and models.
  • Reporting — automated and clear.
  • Data cleaning — reliable inputs.
  • Analysis — trends and insight.
  • Documentation — definitions maintained.
The actual work

A week in the role

A data analyst sits between the source systems and the people who read the report. Much of it is routine: SQL against the warehouse, Power Query cleaning up exports, DAX measures that have to tie back to Xero, and working out why last month's figure changed. The client's managers make the decisions; the analyst makes the numbers defensible.

The taskWhat that actually involves
Publish the weekly reporting pack

Refreshes the Power BI model each Monday, confirms the on-premises gateway ran overnight without failures, ties the totals back to Xero or the source system, and publishes to the workspace before the client's leadership meeting starts.

Write the SQL underneath

Writes and tunes SQL against SQL Server, Postgres, BigQuery or Snowflake — joins, window functions, a date table built on the July-to-June financial year — and keeps queries in a repository so revenue is counted the same way each time.

Clean source data in Power Query

Builds Power Query steps that trim trailing spaces, standardise state and postcode fields, unpivot the finance team's spreadsheet exports and set column types, so a date column does not arrive as text and quietly break every measure downstream.

Write and document DAX measures

Builds the measure layer with CALCULATE and time-intelligence functions over a proper date table — year-to-date, prior-year comparison, rolling average, gross margin — and writes down what each measure counts and which rows it excludes.

Explain why the number moved

When a figure looks wrong, traces it back through the model to the source row: a duplicated invoice, a late-posted journal, a changed product code, a branch that stopped submitting. Reports what actually moved rather than restating the variance.

Build a dashboard people use

Sits with the manager who will use the page to work out which decisions it has to support, then builds it — slicers by region and rep, drill-through to line detail, tooltips — and removes the visuals nobody opens.

Run data quality checks

Runs a standing check before publishing: row counts against source, nulls in key fields, duplicate customer records, orphaned keys, and totals that do not tie to the general ledger — then flags the breaks for the client to resolve.

Model the star schema

Designs fact and dimension tables in the semantic model, sets relationship cardinality and cross-filter direction, hides raw columns from report view, and replaces the bidirectional relationships that were quietly inflating totals in the existing report.

Answer ad hoc data questions

Turns a question like which accounts bought one product but not another last quarter into a query, confirms the definition with whoever asked before running it, and returns an Excel extract or a bookmarked report page rather than a new dashboard.

Join marketing and web data

Connects GA4, Google Ads and Meta Ads into Looker Studio or Power BI alongside CRM records from HubSpot or Salesforce, reconciles the different attribution windows, and notes plainly where the platforms will never agree on a conversion count.

Automate a manual monthly report

Finds the spreadsheet a manager rebuilds by hand each month, reproduces the logic in the model, sets a scheduled refresh and email subscription so it arrives on its own, and retires the old file so two versions stop circulating.

Maintain the metric definitions

Maintains a written definition of every metric — what makes a customer active, whether revenue is stated ex-GST, which date field drives the period — so two reports stop returning two different answers to the same question.

Fix the failed overnight refresh

Works through overnight refresh failures: an expired Xero or Salesforce OAuth token, a renamed source column, a gateway that dropped offline, a query timing out. Repairs the model and restages the refresh before anyone opens the report.

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Questions

Frequently asked

How much does a data analyst cost?
From $14/hr + GST for a full-time, dedicated team member — roughly $29K a year against $95K–$115K all-in for the local equivalent once you add super, leave, payroll tax, software and a desk. No placement fee, no setup fee, no recruitment retainer: you pay from the day they start, for hours worked, and interviewing candidates costs nothing. Specialist roles sit a little higher. Run your numbers →
How fast can they start?
Typically 14 days from your discovery call to day one. In the first week we source and screen against your brief; you get three matched profiles and interview whoever you like. Once you choose, we handle the offer, the contract, equipment and connectivity checks, and induct them on our side before they reach you. Specialist roles — developers, NDIS claims, anything needing niche software — can take a week longer, because we won't pad a shortlist just to hit a date.
What if the fit isn't right?
You're covered twice over. If it's clearly wrong by day five, your first week is refunded in full. After that, a free replacement any time — new shortlist, new interviews, no second fee, because there was never a first one. Before it gets that far, talk to us: our HR manager will work through it with you and the team member, since most problems turn out to be an unclear process rather than the wrong person, and a fortnight of coaching usually fixes it. Replacing someone is the last resort, not the first move.
Is there a minimum term?
Three months, then month to month. It's the same runway you'd give a new local hire to learn your systems, your clients and your standards — and the team members who get a fair run are the ones who stay for years. There are no exit penalties at any point, and if the issue is the person rather than the role, the first-week refund and free replacement cover that separately.
How do you handle confidentiality?
The same way you'd treat any remote team member. Every placement signs an NDA and a confidentiality clause before day one, and they work inside your systems — your email, your CRM, your file storage — so you control what they can see and can revoke access instantly. No client data is stored on our side.
What stays with you, and what goes to them?
They take the recurring, process-driven part of the data Analyst role — the work that happens the same way every week and eats your day. Judgement calls, client relationships, anything requiring your licence, sign-off or authority stay with you. The clients who get the most out of a data Analyst hand over a defined process and keep the decisions, rather than handing over the whole function and hoping. On the discovery call we'll map which tasks fall on which side of that line before you commit to anything.
How do I hand the work over without losing weeks to training?
Record yourself doing the task once and talk through it as you go — a fifteen-minute screen recording beats a written manual every time, and your data Analyst will turn it into a documented process you both work from. Expect the first fortnight to be shadowing and checking, then steadily less. If you have nothing documented, that's normal and it's not a blocker: we'll help you decide what to record first, and your account manager checks in through the whole ramp-up.