Analytics Engineer

CHEP helps move more goods to more people, in more places than any other organization on earth via our 347 million pallets, crates and containers. We employ approximately 13,000 people and operate in 60 countries. Through our pioneering and sustainable share-and-reuse business model, the world’s biggest brands trust us to help them transport their goods more efficiently, safely and with less environmental impact.

What does that mean for you? You’ll join an international organization big enough to take you anywhere, and small enough to get you there sooner. You’ll help change how goods get to market and contribute to global sustainability. You’ll be empowered to bring your authentic self to work and be surrounded by diverse and driven professionals. And you can maximize your work-life balance and flexibility through our Hybrid Work Model .

Job Description

In this role, you will design, implement, and optimise inclusive, high-quality data models and platform performance to enable accurate, efficient analytics and support data-driven decision-making across the organisation.

You will collaborate with diverse stakeholders and empower users through technical support, training, and best-practice guidance, ensuring everyone can confidently access, understand, and maximise the value of the platform.

Key Responsibilities May Include:

Design and implement data models and indexes required to support the platform and ensuring that the data is organized and structured in a way that enables efficient and effective analysis.

Design and implement data models optimized for analytics ensuring high levels of data quality and integrity for accurate analytics outcomes.

Provide technical support to end users, resolving any technical issues that arise, and ensuring that the platform is functioning effectively and efficiently.

Migrate data from existing systems into the platform and ensuring that the data is structured and organized in a way that enables effective analysis.

Monitor the performance of the platform, identifying areas for improvement, and implementing optimizations to ensure that the platform is functioning efficiently and effectively

Providing training and support to end users, helping them to understand and use the platform effectively, and ensuring that they are able to extract the maximum value from the platform.

Stay up to date with the latest developments in the data analytics and business intelligence industries, and ensuring that the platform is configured and optimized to meet the latest standards and best practices.

Collaborate with cross functional stakeholder groups to align data outputs with dynamic business needs

Key Requirements

Semantic modelling + KPI governance

Can design and maintain enterprise KPI definitions and semantic models that remain stable as requirements evolve.

Has operated a modelling / release process, standards, reviews, and safe rollouts for analytics assets.

Lakehouse-first analytics delivery

Comfortable building and supporting analytics assets where Databricks is the consumption plane, and data is structured through Raw/Cleansed/Curated layers on AWS S3.

Works effectively within Unity Catalog governance and quality controls data contracts + monitoring via Soda.

BI platform engineering

Power BI: proven capability to maintain semantic models at scale and implement pragmatic operational practices, model hygiene and repeatable maintenance.

ThoughtSpot: can implement/assess RLS options and manage user/group access patterns.

Demonstrated ability to improve platform reliability via proactive practices (alerts/processes) rather than reactive firefighting.

Engineering discipline for analytics

Uses version control and follows controlled change/release practices for analytics assets; understands why analytics must be treated as production-grade.

Stakeholder delivery

Can translate business questions into durable datasets and explain changes clearly to stakeholders.

Skills and experience

Experience with dbt-like practices (modular models, tests, docs, CI)

Familiarity with Microsoft guidance for Power BI lifecycle management and managing change across environments.

Exposure to BDH ecosystem tools such as Dataiku and catalogue patterns

Awareness of BDH ingestion patterns (e.g., Lakeflow Connect/Boomi) to anticipate downstream impacts.

Remote Type

Hybrid Remote

Skills to succeed in the role

Adaptability, Data Architecture Development, Data Engineering, Data Integration, Data Integrity, Data Modeling, Data Security, Empathy, Experimentation, Microsoft Power Business Intelligence (BI), Python (Programming Language), Tableau (Software), Taking Ownership, Teamwork, Understand Customers

Individuals fraudulently misrepresenting themselves as Brambles or CHEP representatives have scheduled interviews and offered fraudulent employment opportunities with the intent to commit identity theft or solicit money. Brambles and CHEP never conduct interviews via online chat or request money as a term of employment. If you have a question as to the legitimacy of an interview or job offer, please contact us at recruitment@brambles.com.