Chep

1 month ago

Analytics Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Design, implement and optimise data models and platform performance to enable accurate analytics and data-driven decision-making. Collaborate with stakeholders, provide technical support and training, and ensure data quality and governance across a lakehouse analytics stack using Databricks, AWS S3, and BI tools to deliver reliable insights.

Location: Manchester

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Key Responsibilities

•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

Key Requirements

•Semantic modelling + KPI governance: design and maintain enterprise KPI definitions and semantic models that remain stable as requirements evolve.
•Lakehouse-first analytics delivery: comfortable building analytics assets with Databricks on AWS S3, and working within Unity Catalog governance and data contracts.
•BI platform engineering: maintain semantic models at scale in Power BI and manage access patterns in ThoughtSpot; improve platform reliability through proactive practices.
•Engineering discipline for analytics: use version control and follow controlled change/release practices for analytics assets, treating analytics as production-grade.
•Stakeholder delivery: translate business questions into durable datasets and explain changes clearly to stakeholders.

Experience:Data analyticsBICloudAnalytics

Skills:CommunicationProblem-solvingStakeholder managementTrainingTechnical support

Languages:English

Tech Stack:DatabricksAWSS3Unity CatalogSodaPower BIThoughtSpotDbtDataikuLakeflowBoomiPythonTableau

Company Brief

Chep

Provides pooled pallets, crates and containers and supply-chain logistics services to manufacturers, retailers and logistics providers globally, enabling transport, storage and returnable packaging solutions that reduce cost, waste and complexity in multi-party supply chains.

Industry: Logistics

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Valuation: Public Company (Market Cap in USD)

Headquarters: Sydney, Australia

Website LinkedIn

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Chep

1 month ago

Analytics Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: Manchester

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Key Responsibilities

•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

Key Requirements

•Semantic modelling + KPI governance: design and maintain enterprise KPI definitions and semantic models that remain stable as requirements evolve.
•Lakehouse-first analytics delivery: comfortable building analytics assets with Databricks on AWS S3, and working within Unity Catalog governance and data contracts.
•BI platform engineering: maintain semantic models at scale in Power BI and manage access patterns in ThoughtSpot; improve platform reliability through proactive practices.
•Engineering discipline for analytics: use version control and follow controlled change/release practices for analytics assets, treating analytics as production-grade.
•Stakeholder delivery: translate business questions into durable datasets and explain changes clearly to stakeholders.

Experience:Data analyticsBICloudAnalytics

Skills:CommunicationProblem-solvingStakeholder managementTrainingTechnical support

Languages:English

Tech Stack:DatabricksAWSS3Unity CatalogSodaPower BIThoughtSpotDbtDataikuLakeflowBoomiPythonTableau

Company Brief

Chep

Industry: Logistics

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Valuation: Public Company (Market Cap in USD)

Headquarters: Sydney, Australia

Website LinkedIn