Platform Engineer

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., * 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.

• 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.