Data Engineer

Analytics Engineer Power BI | Data Modelling | Semantic Layer | GCP $120-140k base DOE plus super Melbourne / Hybrid A fast-growing data and AI consultancy is looking for a mid-level Analytics Engineer to join its team and work on modern data platforms, analytics solutions and AI-powered products for enterprise clients. The business is building the data foundations that enable organisations to get more value from their data - combining modern data engineering, analytics and AI to create trusted, decision-ready information. This is an opportunity to join at an exciting stage of growth, with the chance to have genuine ownership over the solutions you build and work closely with both technical teams and senior business stakeholders. The Role We're looking for an Analytics Engineer who can own the journey from raw data through to meaningful insights. You'll work across ingestion, transformation, data modelling and the semantic layer, through to Power BI dashboards and visualisations that are actually used by the business. A big part of the role will be understanding why the business needs the data, not simply building what you're given. You'll work directly with stakeholders to understand their use cases, the decisions they're trying to make, and the metrics and dimensions that matter - then translate those requirements into well-designed, reusable data models. You'll be equally comfortable in a requirements workshop as you are working in SQL and the data warehouse. What you'll be doing Design and build end-to-end data pipelines, from ingestion and transformation through to modelling and reportingDesign and maintain semantic layers and dimensional data models that support trusted, self-service analyticsBuild and maintain Power BI dashboards, datasets and visualisationsRun requirements and discovery sessions with business stakeholders to understand use cases, metrics and dimensionsTranslate business requirements into scalable and well-structured data modelsEstablish consistent naming conventions, metric definitions and business logic across analytical modelsWork with modern data engineering tools across ingestion, ELT/ETL, orchestration and transformationUse SQL and transformation frameworks such as dbt to develop reliable analytical datasetsCollaborate with data engineers, data scientists, delivery teams and client stakeholdersApply engineering best practice including version control, testing, CI/CD and documentationContribute reusable data modelling patterns and frameworks to improve how future projects are delivered What we're looking for We're looking for someone with 3–5 years' experience across Analytics Engineering, BI Development or Data Engineering who has taken ownership of data solutions end-to-end. You'll ideally bring: Strong Power BI experience, including datasets, semantic models and dashboard developmentStrong SQL skillsHands-on experience with data modelling, particularly dimensional modellingExperience designing semantic layers, metrics or governed analytical modelsExperience with a modern transformation framework such as dbtExperience with a cloud data warehouse such as BigQuery, Snowflake, Redshift or similarUnderstanding of data engineering fundamentals including ETL/ELT, pipelines and orchestrationExperience with tools such as Airflow, Fivetran, Airbyte or dbt CloudStrong communication skills and confidence working directly with business stakeholdersThe ability to take ambiguous business requirements and turn them into practical technical solutions GCP experience is preferred Experience with GCP and BigQuery would be highly regarded, although candidates coming from AWS or Azure environments with strong underlying data engineering and modelling fundamentals will also be considered. Nice to have AI or LLM-powered analyticsNatural-language querying or conversational BIAgentic analyticsData governance, access controls or data catalogingConsulting or client-facing delivery experienceExperience working across multiple industries or client engagements Why join? You'll be joining a growing data and AI business where analytics engineering sits at the heart of what they build. Rather than simply receiving technical requirements and building dashboards, you'll have the opportunity to work directly with stakeholders, understand their problems and shape the underlying data solution. You'll gain exposure across data engineering, analytics, semantic modelling, BI and emerging AI technologies, while working on projects where the output has a genuine impact on how organisations use their data.