Data Engineer

Talent Insights Group; City of Melbourne; On-site; AUD 110,000 - 150,000; Full time

Job summary

Talent Insights Group is seeking a mid-level Analytics Engineer to own data pipelines, analytics platforms and AI-powered insights for enterprise clients in Australia. The role focuses on end-to-end data solutions, semantic modelling, and Power BI dashboards that business units actively use.

You’ll work with stakeholders to define metrics, dimensions and trusted data models, bridging data engineering, analytics and client delivery across cloud warehouses and modern transformation tools.

Qualifications

• 3–5 years’ experience in Analytics Engineering, BI Development or Data Engineering.
• Strong Power BI experience with datasets, semantic models and dashboard development.
• Hands-on data modelling experience, particularly dimensional modelling.

Responsibilities

• Design and build end-to-end data pipelines from ingestion to reporting.
• Design and maintain semantic layers and dimensional data models.
• Build and maintain Power BI dashboards, datasets and visualisations.
• Run discovery sessions with stakeholders to understand use cases and metrics.
• Translate requirements into scalable, well-structured data models.
• Establish naming conventions, metric definitions and business logic across models.
• Work with modern data engineering tools across ingestion, ELT/ETL, orchestration.
• Use SQL and frameworks such as dbt to develop analytical datasets.
• Collaborate with data engineers, data scientists, delivery teams and clients.
• Apply engineering best practices including version control, testing, CI/CD and documentation.
• Contribute reusable data modelling patterns and frameworks.

Skills

Power BI

Data modelling

Semantic modelling

dbt

ETL/ELT

SQL

Analytics engineering

BI dashboards

Dimensional modelling

Tools

dbt Cloud

Airflow

Fivetran

Airbyte

BigQuery

Snowflake

Redshift

Job description

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 reporting
• Design and maintain semantic layers and dimensional data models that support trusted, self-service analytics
• Build and maintain Power BI dashboards, datasets and visualisations
• Run requirements and discovery sessions with business stakeholders to understand use cases, metrics and dimensions
• Translate business requirements into scalable and well-structured data models
• Establish consistent naming conventions, metric definitions and business logic across analytical models
• Work with modern data engineering tools across ingestion, ELT/ETL, orchestration and transformation
• Use SQL and transformation frameworks such as dbt to develop reliable analytical datasets
• Collaborate with data engineers, data scientists, delivery teams and client stakeholders
• Apply engineering best practice including version control, testing, CI/CD and documentation
• Contribute 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 development
• Hands‑on experience with data modelling, particularly dimensional modelling
• Experience designing semantic layers, metrics or governed analytical models
• Experience with a modern transformation framework such as dbt
• Experience with a cloud data warehouse such as BigQuery, Snowflake, Redshift or similar
• Understanding of data engineering fundamentals including ETL/ELT, pipelines and orchestration
• Experience with tools such as Airflow, Fivetran, Airbyte or dbt Cloud
• Strong communication skills and confidence working directly with business stakeholders
• The 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 analytics
• Natural-language querying or conversational BI
• Agentic analytics
• Data governance, access controls or data cataloging
• Consulting or client‑facing delivery experience
• Experience working across multiple industries or client engagements

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.