Senior Data Platform Engineer — Real-Time & Cloud-Native

Simple Machines Pty Ltd; Greater London; Hybrid; GBP 110,000 - 165,000; Full time

Job summary

Simple Machines is seeking a hands-on Principal Data Engineer to lead platform and architecture design for cloud-native data platforms, applying data mesh concepts and data contracts.

You will build real-time pipelines with Spark, Databricks, Snowflake on AWS/GCP, mentor teams, and work directly with clients to deliver measurable outcomes.

This role blends technical leadership with hands-on delivery in a consulting setting, offering autonomy and the chance to shape modern data architectures.

Qualifications

• Strong Python and SQL
• Experience owning large-scale data platform architectures
• Deep experience with Spark and modern data platforms (Databricks/Snowflake)
• Cloud data services (AWS or GCP)
• Infrastructure-as-code (Terraform, Pulumi)
• CI/CD pipelines (GitHub Actions, ArgoCD)
• Data testing/quality frameworks (dbt, Great Expectations, Soda)
• Consulting or professional services background
• Mentoring senior engineers and shaping technical culture

Responsibilities

• Lead end-to-end architecture of cloud-native data platforms
• Design scalable data ecosystems using data mesh, data products, data contracts
• Build and optimise batch and real-time pipelines
• Own data storage & performance across relational/noSQL/analytical stores
• Ensure security, governance, and production-readiness by design
• Consult with clients to translate business needs into pragmatic engineering decisions
• Mentor engineers and set engineering standards across teams

Skills

Python

SQL

Spark

Data mesh

Data contracts

Cloud platforms

Tools

Databricks

Snowflake

AWS

GCP

Terraform

Pulumi

GitHub Actions

ArgoCD

dbt

Great Expectations

Soda

Airflow

Job description

Simple Machines is seeking a hands-on Principal Data Engineer to lead platform and architecture design for cloud-native data platforms, applying data mesh concepts and data contracts.

You will build real-time pipelines with Spark, Databricks, Snowflake on AWS/GCP, mentor teams, and work directly with clients to deliver measurable outcomes.

This role blends technical leadership with hands-on delivery in a consulting setting, offering autonomy and the chance to shape modern data architectures.