Lead DevOps Engineer (AWS/Snowflake)

Luxoft
London, UK
about 1 month ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source

Tech stack

Amazon Web Services Microsoft Azure Cloud Computing Cloud Computing Security Continuous Delivery Continuous Integration Data as a Services Information Engineering Data Infrastructure Extract Transform Load (ETL) Data Warehousing DevOps
+29 more
Github Monitoring of Systems Identity and Access Management Key Management Role-Based Access Control Release Management Prometheus Data Streaming Datadog Data Logging Data Ingestion System Availability Delivery Pipeline Snowflake Grafana Git Cloudformation Containerization Gitlab-ci Kubernetes Infrastructure Automation Frameworks Deployment Automation Real Time Data Apache Kafka Data Management Terraform Software Version Control Serverless Computing Docker

Job description

We are looking for a skilled DevOps Engineer to build and operate the cloud infrastructure, automation, and deployment pipelines underpinning our next-generation Snowflake data warehouse and integration platform.

This role is critical to ensuring our data platform is secure, scalable, and reliably delivered through modern DevOps practices. You will work closely with data engineers, architects, and the project team to enable continuous delivery, environment consistency, and operational excellence across the platform.

Responsibilities

Infrastructure & Platform Engineering

Design and manage cloud infrastructure supporting Snowflake and associated data services

Implement infrastructure-as-code (IaC) using tools such as Terraform or CloudFormation

Ensure environments (dev/test/prod) are consistent, secure, and scalable

CI/CD & Automation

Build and maintain CI/CD pipelines for data platform components (e.g., Snowflake objects, dbt models, ingestion pipelines)

Automate deployment, testing, and promotion of code across environments

Integrate version control and release management processes

Snowflake Enablement

Support automated provisioning and configuration of Snowflake environments

Manage role-based access control, secrets, and environment isolation

Collaborate with data engineers to optimize deployment patterns for Snowflake workloads

Monitoring & Reliability

Implement monitoring, logging, and alerting across the data platform

Ensure high availability and performance of pipelines and integrations

Troubleshoot production issues and drive root cause analysis

Security & Compliance

Embed security best practices across infrastructure and pipelines

Manage secrets, encryption, and access controls in line with financial services standards

Support audit and compliance requirements for client and regulatory needs

Collaboration & Best Practices

Work closely with engineering teams to promote DevOps culture and practices

Define standards for deployment, branching, and environment management

Contribute to documentation and knowledge sharing across the team

Requirements

Must have

Experience with Snowflake

DevOps & Cloud Engineering

Strong experience in DevOps or platform engineering roles

Hands-on experience with AWS

Proven use of infrastructure-as-code tools (e.g., Terraform)

CI/CD & Tooling

Experience building CI/CD pipelines using tools such as GitHub Actions, GitLab CI, or Azure DevOps

Strong understanding of version control (Git) and release management practices

Data Platform Awareness

Experience supporting data platforms or data engineering teams

Understanding of ELT/ETL pipelines and data workflows

Monitoring & Operations

Experience with monitoring and observability tools (e.g., Prometheus, Grafana, Datadog, or cloud-native services)

Strong troubleshooting and incident management skills

Security

Knowledge of cloud security best practices, IAM, and secrets management

Awareness of compliance requirements in regulated environments

Nice to have

Experience with dbt and modern data stack tooling

Familiarity with containerization (Docker, Kubernetes)

Exposure to streaming or real-time data technologies (e.g., Kafka)

Experience in financial services or asset management environments

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