Data Analytics Intern

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 Visualisation & Business Intelligence: Microsoft Power BI, Tableau, Looker, Excel dashboards.
• Database Management: MySQL, PostgreSQL, Microsoft SQL Server, Oracle Database.
• 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.
• ETL & Data Integration: ETL/ELT processes, data transformation, data pipelines, API integration.
• Cloud & Data Platforms: Microsoft Azure, AWS, Google Cloud Platform, Snowflake, Databricks, BigQuery.
• Statistics & Analytics: Hypothesis testing, regression analysis, correlation, forecasting, trend analysis.
• Automation: Python scripting, SQL automation, Power Automate, scheduled reporting.
• Version Control & Collaboration: Git, GitHub, Jira, Agile methodologies.
• 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 Modern 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.