Hiring: Data Analyst | Remote - Australia

We are hiring a skilled and analytical professional on behalf of one of our clients for a fully remote opportunity.

The ideal candidate will have strong analytical and problem-solving skills, hands-on experience with data analytics tools, and the ability to transform complex datasets into meaningful insights that support strategic business decisions.

Job Title: Data Analyst

Location: Australia

Key Responsibilities

- Collect, extract, clean, validate, and analyse large datasets from multiple sources.
- Perform exploratory data analysis (EDA) to identify trends, patterns, anomalies, and business opportunities.
- Develop and maintain interactive dashboards, reports, and visualisations using Power BI, Tableau, or similar tools.
- Write and optimise SQL queries to retrieve, join, aggregate, and manipulate data from databases.
- Use advanced Excel functions, PivotTables, and Power Query for data analysis and reporting.
- Apply Python or R for data manipulation, statistical analysis, and workflow automation.
- Translate business requirements into actionable insights and data-driven recommendations.
- Monitor key performance indicators (KPIs) and prepare reports to measure business performance.
- Conduct root cause analysis to identify performance gaps and recommend corrective actions.
- Perform trend analysis, variance analysis, and benchmarking to support business planning.
- Automate recurring reports and analytical workflows to improve efficiency and accuracy.
- Collaborate with business stakeholders, finance teams, operations teams, and technical teams.
- Develop and maintain data models and relationships across multiple datasets.
- Conduct data reconciliation and investigate discrepancies between data sources.
- Support forecasting, budgeting, demand planning, and business performance analysis.
- Identify opportunities to improve reporting processes and data collection methods.
- Present analytical findings through reports, dashboards, and presentations.
- Work with data engineering teams to improve data pipelines and data availability.
- Establish data quality checks to ensure accuracy, completeness, and consistency.
- Perform ad hoc analysis to support business-critical decisions.
- Analyse customer behaviour, sales performance,



and operational metrics to identify growth opportunities.
- Support data warehouse, data mart, and business intelligence initiatives.
- Maintain documentation for data sources, analytical methodologies, and reporting procedures.
- Ensure data confidentiality and compliance with applicable data protection requirements.
- Manage multiple analytical projects and reporting deadlines while maintaining high-quality standards.

Technical Skills

- Programming & Query Languages: SQL, Python, R.
- Data Manipulation & Analysis: Pandas, NumPy, SciPy, statistical analysis, exploratory data analysis.
- Microsoft Excel: Advanced formulas, PivotTables, XLOOKUP, VLOOKUP, Power Query, data validation.
- Data Modelling: Relationships, star schema, snowflake schema, dimensional modelling.
- Statistics & Analytics: Hypothesis testing, regression analysis, correlation, forecasting, trend analysis.
- Data Governance: Data quality management, metadata, data lineage, access controls, data privacy.

Required Skills & Qualifications

- Strong analytical thinking, logical reasoning, and problem-solving abilities.
- Proficiency in SQL and experience querying and analysing relational databases.
- Hands‑on experience with Excel and data visualisation tools such as Power BI or Tableau.
- Understanding of data cleaning, transformation, validation, and reporting processes.
- Knowledge of statistics, KPI measurement, and business performance analysis.
- Ability to interpret complex datasets and present findings clearly.
- Strong attention to detail and commitment to data accuracy.
- Excellent written and verbal communication skills.
- Ability to explain analytical findings to technical and non‑technical stakeholders.
- Ability to work independently and collaboratively in a remote environment.
- A degree in Data Analytics, Data Science, Statistics, Mathematics, Computer Science, Business Analytics, or a related field is preferred.





Preferred Qualifications

- Experience using Python libraries such as Pandas, NumPy, SciPy, and Matplotlib.
- Advanced Power BI skills, including DAX, Power Query, data modelling, and dashboard optimisation.
- Experience creating interactive Tableau dashboards and visualisations.
- Familiarity with ETL/ELT processes and data integration from multiple systems.
- Knowledge of data warehousing, dimensional modelling, and database optimisation.
- Experience with cloud platforms such as Azure, AWS, or Google Cloud Platform.
- Familiarity with Snowflake, Databricks, Google BigQuery, or Amazon Redshift.
- Knowledge of hypothesis testing, regression analysis, and predictive analytics.
- Experience automating reports using Python, SQL, or Power Automate.
- Familiarity with APIs, third‑party data integrations, and large datasets.
- Understanding of data governance, data security, and UK GDPR principles where applicable.
- Experience with Agile methodologies and project management tools.
- A portfolio of analytics projects, dashboards, or business intelligence solutions is an advantage.

What You Will Gain

- Remote Working Opportunity: Work remotely from within the United Kingdom.
- Real-World Business Exposure: Contribute to data-driven projects that address practical business challenges.
- Technical Skill Development: Strengthen your expertise in SQL, Python, Excel, Power BI, Tableau, and modern analytics tools.
- Cross-Functional Collaboration: Work with professionals across business, operations, finance, and technology teams.
- Analytical Problem-Solving: Develop your ability to turn complex data into meaningful business recommendations.
- Exposure to Contemporary Technologies: Gain opportunities to work with cloud platforms, data warehouses, and automation tools, depending on project requirements.
- Professional Growth: Enhance your communication, stakeholder management, reporting, and analytical decision-making skills.
- Process Improvement Experience: Contribute to improving data quality, reporting efficiency, and business workflows.
- Career Development: Build practical experience in data analytics and business intelligence within a professional environment.

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