Platform Architect: Azure Databricks & FinOps Lead

HelloKindred; England; Hybrid; GBP 85,000 - 125,000; Full time

Job summary

HelloKindred, a specialist staffing partner for tech and creative roles, is seeking a Platform Architect to enhance an enterprise Data Platform on Azure Databricks. The role involves hands-on architecture, engineering, operational support, and platform governance to enable serverless databricks capabilities and cost optimisation.

The successful candidate will drive FinOps practices, tagging standards, and scalable data ingestion using Python, PySpark, SQL, and Delta Lake.

Qualifications

• Hands-on experience implementing Azure Databricks in production.
• Strong Databricks Serverless, workload placement and performance tuning.
• Experience with Azure networking, identity, security and monitoring.
• Proficient Python, PySpark and SQL development in large data environments.
• Knowledge of FinOps, cost attribution, budgeting and governance.

Responsibilities

• Assess workloads and select appropriate compute models (Serverless, Jobs, Interactive).
• Configure Databricks Serverless across notebooks, jobs, SQL workloads and pipelines.
• Define workload placement standards and cost-effective use cases for Serverless.
• Implement compute policies, autoscaling, quotas, budgets and guardrails.
• Monitor platform performance and costs, identify inefficiencies.
• Deliver end-to-end data flows and secure integrations for analytics.

Skills

Databricks Serverless

Azure Databricks

Python

PySpark

SQL

FinOps

Data Governance

CI/CD

Azure Networking

Security

Education

Bachelor's degree in CS/ENG

Tools

REST APIs

Terraform

CI/CD

Job description

HelloKindred, a specialist staffing partner for tech and creative roles, is seeking a Platform Architect to enhance an enterprise Data Platform on Azure Databricks. The role involves hands-on architecture, engineering, operational support, and platform governance to enable serverless databricks capabilities and cost optimisation.

The successful candidate will drive FinOps practices, tagging standards, and scalable data ingestion using Python, PySpark, SQL, and Delta Lake.