Platform Engineer

Harvey Nash Group; Remote; GBP 80,000 - 100,000; Full time

Job summary

A leading technology consulting firm in the UK is looking for a Contract Platform Engineer to join their Data Engineering team. In this remote role, you will leverage your SQL expertise to design solutions and develop data pipelines. Your responsibilities will include collaborating with product owners, building CI/CD pipelines, and managing cloud infrastructure across various platforms. Experience with Microsoft Azure and Terraform is essential, while familiarity with automation and data quality practices is desirable. This is an excellent opportunity for established engineers eager to drive innovation.

Qualifications

• Strong expertise with SQL is essential.
• Experience with infrastructure as code tools like Terraform or Ansible.
• Ability to create maintainable data pipelines for ingestion and transformation.
• Demonstrated experience with Microsoft Azure and Microsoft Fabric.
• Experience in BI tools and data processing frameworks, preferably using Python or Scala.
• Deep understanding of CI/CD workflows and automation tools.

Responsibilities

• Work closely with product owners to understand data requirements.
• Develop reports and visualizations to derive value from data.
• Design and manage cloud infrastructure for data workloads.
• Build and maintain CI/CD pipelines for SQL deployment.

Skills

Strong expertise with SQL

Experience defining infrastructure with Terraform

Ability to design, build, and maintain data pipelines

Experience in Microsoft Azure

Experience with Apache Spark using Python

Working within cloud environments

Knowledge of version control with git

Knowledge of CI/CD methodologies

Tools

Terraform

GitHub Actions

GitLab CI

Docker

Kubernetes

Job description

Platform Engineer | Outside IR35 | Remote | Starting ASAP

Day Rate: £400

Harvey Nash's Client require a contract Platform Engineer, You'll be working as a part of a team within Data Engineering and closely with software engineering teams and architects to deliver strategic data solutions, while driving Agile and DevOps adoption in the delivery of data engineering.

Responsibilities

• Working closely with the product owners to understand their data requirements and designing solutions for the same.
• Enable product owners and management to derive value through modelling, sourcing and data transformation.
• Enable product owners to understand the uptake of various products by building reports and visualisations from data.
• Developing comprehensive knowledge of the data structures and metrics, advocating change where needed.
• Educating and embedding new data techniques into the business through role modelling, training and experiment design oversight.
• Delivering maintainable data engineering pipelines by following the best practices through the designated route-to-live environments.
• Design, deploy, and manage cloud infrastructure (AWS/Azure/GCP) for data workloads using Terraform or CloudFormation.
• Build and maintain CI/CD pipelines (GitHub Actions/GitLab CI) to automate the testing and deployment of SQL.

Essential Skills & Experience

• Strong expertise with SQL.
• IaC Tools: Experience defining infrastructure with Terraform, Ansible, or Pulumi.
• Ability to design, build, and maintain data pipelines for data ingestion and transformation
• Demonstrable experience in Microsoft Azure and Microsoft Fabric (e.g. Data Factory, Azure SQL).
• Experience of BI tools and Data processing frameworks such as Apache Spark - preferably using Python (PySpark) or Scala.
• Experience working within cloud environments. Although Azure is preferred, AWS and GCP are also valuable.
• Knowledge of version control working with git (GitLab, GitHub, Bitbucket, etc.)
• Deep knowledge of Git flow, CI/CD methodologies, and automation tools (Jenkins, GitHub Actions, etc.).

Desirable Skills/Experience

• Experience with Automation Testing and Test-Driven Development.
• Configuration management and containerization tools (e.g., Docker, Kubernetes).
• Experience or interest in Data Science.
• Understanding of Data Quality and Data Governance best practices.
• Experience with monitoring and logging tools.