BLACK OPS SOLUTIONS · IT Graduate IT Interview PackAU · 2026

Data Engineer / Analyst · graduate level · Australia

Graduate Data Engineer / Analyst

Turns raw operational data into numbers the business will actually act on.

Job description · fictional employer

Graduate Data Engineer / Analyst

Yarrow Energy Retail

Location
Brisbane - hybrid, 2 days in office
Employment type
Full-time, permanent - 12-month graduate program
Salary
AUD $80,000 base + 12% superannuation
Reports to
Data Platform Lead
Intake
February 2027 - applications close 10 October 2026

About us

Yarrow Energy Retail sells electricity and gas to about 210,000 households and small businesses across Queensland and New South Wales. Every one of them generates meter reads, billing events, payments and service calls. Our data team turns that into pricing decisions, hardship identification, regulatory reporting and the forecasts the trading desk relies on.

The team you would join

The data group is twelve people: five data engineers, four analysts, two analytics engineers and a lead. You would split the first year across engineering and analytics rather than choosing on day one, because the best people in this field can do both and most graduates do not yet know which they prefer.

What you will do

  • Build and maintain data pipelines in Python and SQL, orchestrated in Airflow
  • Write dbt models with tests and documentation - an untested model does not get merged
  • Investigate data quality issues end to end, from a stakeholder saying the number looks wrong to a fix in the source
  • Build and maintain Power BI reports that people actually open, and retire the ones they do not
  • Work directly with billing, hardship and trading teams to understand what a number is for before you produce it
  • Support regulatory reporting cycles, where accuracy and traceability are non-negotiable
  • Contribute to the data dictionary and lineage documentation
  • Present findings to non-technical stakeholders, including saying when the data cannot answer the question

What we are looking for

  • A completed or in-progress bachelor degree in data science, computer science, IT, mathematics, statistics, engineering, economics or a related discipline
  • SQL you can defend in an interview - joins, group by, having, window functions or a demonstrated willingness to learn them fast
  • Python for data work: pandas or equivalent, reading awkward files, basic scripting
  • The habit of questioning a result that looks too good
  • Clear communication in writing. Half of analytics is explaining a number to someone who did not ask for the caveats
  • Attention to detail - in energy retail, a wrong number becomes a wrong bill
  • Full Australian working rights

Nice to have

  • Exposure to a cloud data warehouse - Snowflake, BigQuery, Redshift or Databricks
  • dbt, Airflow or any orchestration tool
  • Power BI, Tableau or Looker
  • Statistics beyond an introductory unit - regression, hypothesis testing, time series
  • Any exposure to the energy sector, or to a regulated industry
  • Version control for analysis work, not just for software

Our stack

SnowflakedbtApache AirflowPython (pandas, Polars)SQLPower BIAWS S3FivetranGreat ExpectationsGit

What the program gives you

  • Rotation across data engineering and analytics in the first year, then you choose
  • A named business stakeholder from month two, so you learn the domain and not just the tables
  • dbt and Snowflake certification paid for, with study time
  • $2,000 learning budget
  • A team that writes tests for data and treats analysis code like code

How the process runs

  1. 1

    Application

    CV plus a link to any analysis you have done, in any format.

  2. 2

    SQL screen

    45 minutes, live but collaborative. Realistic messy tables, and we help if you get stuck.

  3. 3

    Case exercise

    Take-home, around three hours. A dataset with deliberate problems in it, and a business question.

  4. 4

    Case discussion

    60 minutes - present your findings to two people, one of whom is not technical.

  5. 5

    Team interview

    45 minutes - stakeholder management, judgement, how you handle being asked for a number you do not trust.

  6. 6

    Offer

    Within a week of the final stage.

The best graduate analysts we have hired were not the ones with the most tooling on their CV. They were the ones who asked why a number was being requested before producing it. Reasonable adjustments are available at any stage.

Example CV · fictional candidate

Ella Marchetti

Written to the job description on the previous tab. Notes on the right explain each choice.

Ella Marchetti

Graduate Data Engineer / Analyst

Brisbane QLD · 0400 000 000 · e.marchetti@example.com · github.com/ellamarchetti · linkedin.com/in/ella-marchetti

Professional summary

Information technology and business graduate with a data specialisation, six months of commercial analytics experience, and a habit of checking the denominator before sharing the number. Strong SQL, working dbt and Airflow exposure, and enough business background to ask what a metric is going to be used for.

Technical skills
SQL
Advanced - window functions, CTEs, query tuning, Snowflake and PostgreSQL
Python
pandas, NumPy, matplotlib, requests, openpyxl
Data engineering
dbt (models, tests, docs), Apache Airflow (basic), Fivetran, Git
Warehousing
Snowflake, PostgreSQL, dimensional modelling (Kimball basics)
Visualisation
Power BI (DAX basics), Tableau, Excel to an advanced level
Statistics
Regression, hypothesis testing, time series decomposition (university level)
Education
Bachelor of Information Technology / Bachelor of Business Management (dual degree), Data Analytics major
Feb 2023 - Nov 2026

The University of Queensland

  • GPA 6.0 / 7
  • Relevant courses: Database Systems (7), Data Analytics (7), Statistical Modelling (6), Information Systems (6), Managerial Accounting (6)
  • Capstone: demand forecasting for a not-for-profit food relief service. Model reduced weekly over-ordering by an estimated 12% in a four-week trial
Experience
Data Analytics Intern
Nov 2025 - Feb 2026 (12 weeks)

Fernhill Insurance Group, Brisbane

  • Rebuilt the weekly claims report in Power BI, cutting preparation from 6 hours of manual Excel work to a 10-minute refresh
  • Wrote 22 dbt models with tests for a claims mart, including the first uniqueness and freshness tests the team had
  • Traced a persistent discrepancy between two claims reports to a duplicated broker record, which had been overstating one region's claim count by 8% for around a year
  • Presented findings twice to a non-technical operations forum of 15 people
Business Analytics Assistant (casual, 12 hrs/week)
Mar 2025 - present

UQ Student Services

  • Automated a monthly participation report from a manual spreadsheet process into a scheduled Python job with a documented data dictionary
  • Built the SQL views three staff members now use directly instead of requesting extracts
Assistant Manager (casual, then part-time)
Feb 2022 - Jan 2025

Riverbend Cafe, Brisbane

  • Managed rosters and stock ordering for a team of nine while studying full-time
  • Introduced a simple sales-by-hour tracking sheet that cut weekly food waste by around 15%
Projects
Queensland electricity demand explorer
Python, dbt, DuckDB, Streamlit, public AEMO data
  • Ingested five years of public half-hourly demand and price data, modelled it in dbt with tests, and published an interactive explorer
  • Documented three data quality issues in the raw feed, including a daylight-saving duplication that silently added 48 rows twice a year
  • github.com/ellamarchetti/qld-demand
Food relief demand forecasting (capstone)
Python, scikit-learn, statsmodels
  • Compared a seasonal naive baseline against regression and gradient boosting; the simplest model that beat baseline was chosen deliberately over the most accurate one
  • Delivered a one-page instruction sheet so volunteers could run it without me
Leadership and activities
  • Treasurer, UQ Data Science Society, 2025 - 2026. Managed a $9,000 annual budget and reported to a committee of eight
  • Volunteer data support, Brisbane community food relief service, 2024 - present
Certifications
  • dbt Fundamentals, 2025
  • Microsoft Power BI Data Analyst Associate (PL-300), April 2026
Referees

Available on request.