Analytics Engineer
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Before you apply
LocationMelbourne
Work modehybrid
Typefull-time
SeniorityMid
Experience3–5 yrs
DepartmentAnalytics
Company size2+ people
PostedSep 22, 2026 · 1mo ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
3-5 years' hands-on experience as an analytics engineer, BI developer or data engineer
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
Understanding of data pipeline orchestration and ELT/ETL tooling (e.g. Fivetran, Airbyte, Airflow, dbt Cloud)
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
Skills
SQL
dbt
Snowflake
BigQuery
Redshift
Power BI
Tableau
Looker
Fivetran
Airbyte
Airflow
dbt Cloud
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
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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.
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Apply data modelling best practice: consistent naming, a business glossary, and clear metric definitions, so models are trusted and reused across engagements.
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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.
Legal
By applying for a role with us, you agree that we will collect and handle your personal information in accordance with our Privacy Policy, available at https://xephyr.co/policy.
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