1 day ago

Platform Engineer – Data Science & AI Platform

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Build and evolve a data science & AI platform that standardises data engineering workloads and traditional ML workflows across teams. Implement infrastructure as code, CI/CD, and environment management for consistent, reproducible pipelines and model serving. Develop shared platform components using Python and Spark, contribute to data/ML lifecycle services (incl. Unity Catalog), and support AgentOps capabilities with observability, reliability, and secure-by-default access controls. Partner with data and ML engineers to drive adoption and best practices.

Location: London

Workplace: Hybrid

Employment Type: Full time · Permanent

Job Function: DevOps, Cloud & Infrastructure

Seniority: Mid level

Key Responsibilities

•Build and evolve the platform (infrastructure and reusable abstractions) that standardises data engineering workloads and ML workflows across teams.
•Implement platform-level Infrastructure as Code, CI/CD, and environment management to support consistent, reproducible workloads across dev/test/prod.
•Build and maintain components using Python and Spark for data processing, shared datasets, and platform services.
•Contribute to shared services for data and ML lifecycle management (pipelines, experiment tracking, versioning, lineage, permissions) aligned to enterprise governance such as Unity Catalog.
•Support AgentOps by implementing and operating an LLM gateway/tool integration capability, agent lifecycle and safety controls, and observability across data & ML Ops and Agent Ops.

Pay and Benefits

Perks:Paid LeaveMedical CareLearning Budget

Key Requirements

•Experience in data platform, data engineering, cloud engineering, or ML platform engineering roles with exposure to Azure.
•Strong hands-on experience with Python and Apache Spark.
•Experience with Azure data platform technologies such as Azure Databricks, ADLS Gen2, and Unity Catalog.
•Working knowledge of security and access management (RBAC, ACLs, identity concepts such as Entra ID).
•Familiarity with Infrastructure as Code using Terraform and experience with CI/CD (Azure DevOps, GitHub Actions).

Experience:Data engineeringCloud engineeringML platform engineering

Skills:CommunicationCollaborationLearning mindsetContinuous improvement

Languages:English

Tech Stack:PythonSparkApache SparkAzureAzure DatabricksADLS Gen2Unity CatalogRBACACLsEntra IDTerraformCI/CDAzure DevOpsGitHub ActionsVNetsNSGsPrivate EndpointsDockerKubernetesLLM gateway

Company Brief

ASOS

ASOS plc is a UK-based online fashion and beauty retailer selling thousands of branded and own-label products worldwide through its e-commerce platform, targeting young adult customers with fast-fashion, marketplace third-party brands, and integrated logistics and marketing services.

Industry: E-commerce

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: London, United Kingdom

Founded: 2000

Glassdoor: 3.4

Website LinkedIn Glassdoor

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ASOS

1 day ago

Platform Engineer – Data Science & AI Platform

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Location: London

Workplace: Hybrid

Employment Type: Full time · Permanent

Job Function: DevOps, Cloud & Infrastructure

Seniority: Mid level

Key Responsibilities

•Build and evolve the platform (infrastructure and reusable abstractions) that standardises data engineering workloads and ML workflows across teams.
•Implement platform-level Infrastructure as Code, CI/CD, and environment management to support consistent, reproducible workloads across dev/test/prod.
•Build and maintain components using Python and Spark for data processing, shared datasets, and platform services.
•Contribute to shared services for data and ML lifecycle management (pipelines, experiment tracking, versioning, lineage, permissions) aligned to enterprise governance such as Unity Catalog.
•Support AgentOps by implementing and operating an LLM gateway/tool integration capability, agent lifecycle and safety controls, and observability across data & ML Ops and Agent Ops.

Pay and Benefits

Perks:Paid LeaveMedical CareLearning Budget

Key Requirements

•Experience in data platform, data engineering, cloud engineering, or ML platform engineering roles with exposure to Azure.
•Strong hands-on experience with Python and Apache Spark.
•Experience with Azure data platform technologies such as Azure Databricks, ADLS Gen2, and Unity Catalog.
•Working knowledge of security and access management (RBAC, ACLs, identity concepts such as Entra ID).
•Familiarity with Infrastructure as Code using Terraform and experience with CI/CD (Azure DevOps, GitHub Actions).

Experience:Data engineeringCloud engineeringML platform engineering

Skills:CommunicationCollaborationLearning mindsetContinuous improvement

Languages:English

Tech Stack:PythonSparkApache SparkAzureAzure DatabricksADLS Gen2Unity CatalogRBACACLsEntra IDTerraformCI/CDAzure DevOpsGitHub ActionsVNetsNSGsPrivate EndpointsDockerKubernetesLLM gateway

Company Brief

ASOS

Industry: E-commerce

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: London, United Kingdom

Founded: 2000

Glassdoor: 3.4

Website LinkedIn Glassdoor