Snowflake Data Platform Engineer

Schroders; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

Schroders is seeking a Data Platform Engineer in London to own and evolve the Snowflake data platform, ensuring reliability, performance and cost‑effectiveness. You will design data models and data products, manage access, and implement governance.

You will build monitoring, automation and alerts, apply ML for anomaly detection, and support delivery with scalable data pipelines across ingestion and orchestration tools.

Qualifications

• Hands-on data engineering on a production scale data platform.
• Strong Snowflake capabilities including RBAC, tasks, streams, and cost control.
• Solid data warehousing and dimensional modelling understanding.
• Proficient in Python and SQL for production pipelines.
• Experience building monitoring, alerting and data quality checks.
• Familiarity with CI/CD, Git workflows and regulated environments.
• Understanding of data governance and privileged access controls.

Responsibilities

• Own and evolve the Snowflake data platform, ensuring reliability and cost‑effectiveness.
• Design data models and reusable data products for platform users.
• Manage access to the platform and enforce data governance.
• Build visibility into health, freshness, quality and cost across pipelines.
• Automate detection, alerts and safe recovery for production issues.
• Lead architectural decisions and mentor junior engineers.

Skills

Data engineering

Snowflake

Python

SQL

Monitoring

Data governance

CI/CD

Security & access management

Data modelling

Cloud AWS

Tools

Ansible

Apache NiFi

Cribl

Docker

Kubernetes

AWS S3

AWS Lambda

Step Functions

SageMaker

ServiceNow

Entra ID

Active Directory

Power BI

Streamlit

Snowflake Certification

Job description

Schroders is seeking a Data Platform Engineer in London to own and evolve the Snowflake data platform, ensuring reliability, performance and cost‑effectiveness. You will design data models and data products, manage access, and implement governance.

You will build monitoring, automation and alerts, apply ML for anomaly detection, and support delivery with scalable data pipelines across ingestion and orchestration tools.