Analytics Engineer
xephyr · Melbourne ·
- Work mode
- Hybrid
- Seniority
- Middle
- Category
- Data analytics
- Experience
- 3+ years
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Mid-level Analytics Engineer at Xephyr (Melbourne, on-site) who owns the full data pipeline for client engagements: ingestion, transformation with dbt, semantic/dimensional modelling in cloud warehouses like Snowflake, and BI dashboards in tools like Power BI or Looker. A core part of the job is running requirements workshops directly with business stakeholders.
Introduction
Xephyr builds sovereign AI agents and the data platforms that power them, for enterprises including Wesfarmers, Telstra, Bupa, Kmart, Garvan Institute and Sunnyfield. Your data doesn't move. Your governance rules apply. Every agent runs inside your environment. We build three things: the data foundations and business context agents need, custom agents trained on client data and workflows, and Xavier, our analytics agent that delivers trusted answers from data fast. If you want to get in on the ground floor of a fast-paced startup where your work has a direct impact on the success of our mission, we'd love to hear from you.
Role summary
We are looking for a mid-level Analytics Engineer to build the end-to-end pipelines that turn raw client data into trusted, decision-ready analytics. You will own the full chain: ingestion, transformation, semantic and data modelling, through to the dashboards and visualisations the business actually uses.
A defining part of this role is working directly with the business to gather requirements. You will run discovery with stakeholders to understand their use cases, the decisions they need to make, and the measures and dimensions that matter, then translate that into a well-structured semantic model. You are equally comfortable in a requirements workshop and in the warehouse, and you know that a good pipeline is only as good as the business logic it encodes.
Responsibilities and duties
Design and build end-to-end data pipelines: ingestion, transformation, semantic and data modelling, through to the visualisation and reporting layer.
Run requirements-gathering sessions directly with the business to capture use cases, key decisions, and the measures and dimensions that should sit in the semantic model.
Design and maintain semantic layers and dimensional data models that support self-serve analytics and Xavier, our analytics agent.
Build and maintain dashboards and visualisations that answer the business questions surfaced during requirements work, not just the ones that were easiest to build.
Apply data modelling best practice: consistent naming, a business glossary, and clear metric definitions, so models are trusted and reused across engagements.
Work across the modern data stack: ingestion and ELT tooling, orchestration, transformation frameworks (e.g. dbt), and cloud data warehouses such as Snowflake.
Collaborate with data engineers, data scientists, delivery leads and client stakeholders to keep technical design aligned to business objectives.
Follow and champion efficient, repeatable and scalable engineering processes (version control, testing, CI/CD, documentation).
Contribute reusable patterns, semantic model templates and delivery accelerators back into Xephyr's IP and the Xavier product.
Ideal candidate
3-5 years' hands-on experience as an analytics engineer, BI developer or data engineer, with demonstrated ownership of a pipeline end to end, from ingestion through to visualisation.
Strong SQL and hands-on experience with a modern transformation framework (e.g. dbt) and a cloud data warehouse (Snowflake, BigQuery, Redshift or similar).
Proven experience designing semantic models or metrics layers, and translating business requirements, use cases, measures and dimensions, into data model design.
Experience with at least one enterprise BI or visualisation tool (Power BI, Tableau, Looker) building dashboards on top of a governed semantic layer.
Confident running requirements workshops directly with business stakeholders, not just working from a technical spec handed down to you.
Understanding of data pipeline orchestration and ELT/ETL tooling (e.g. Fivetran, Airbyte, Airflow, dbt Cloud).
Nice to haves or wanting to learn on the job
Exposure to AI or LLM-powered analytics, agentic BI, or natural-language query layers.
Experience working in a consulting or client-facing delivery environment across multiple industries.
Familiarity with data governance, access control and data cataloguing tools.
Our culture and core values
As we are still in our early stages, we believe cultivating our culture and core values is going to be critical to the success of our business. Our core values are human progress, iterate quickly, further together, be dependable, and have fun. We are looking for individuals who are attracted to these values and wanting to help shape our culture as we grow.
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