Software Engineer Data

About The Role

We're building the data platform that powers decision-making across PRYPCO. As a Software Engineer (Data), you'll design and operate the systems that make data reliable, accessible, and easy to work with for every team that depends on it.

You'll own problems end-to-end, from architecture to automation, and partner closely with the people who use what you build.

Key Responsibilities

• Design, build, and maintain efficient, reliable data platforms, streamlining end-to-end data pipelines and automating manual workflows.
• Partner with cross-functional teams (Product, Engineering, and Data Science) to translate ambiguous requirements into practical, scalable solutions.
• Establish and enforce data standards, maintain comprehensive documentation, and manage the company-wide data registry.
• Onboard and support platform users while communicating updates and insights through dashboards, bots, and other internal tools.
• Plan and execute organisation-wide platform improvements, defining best practices for coding, testing, deployment, and maintenance.
• Use data to guide engineering decisions and continuously improve platform performance and reliability.
  
  

• Bachelor's or Master's degree in Computer Science or a related field, or equivalent practical experience.
• Strong proficiency in Python, SQL, and Unix shell scripting.
• Hands-on experience with Agile engineering practices, including TDD, refactoring, CI/CD, and XP.
• Proven experience designing, implementing, and maintaining custom ETL pipelines.
• Experience with workflow orchestration tools such as Apache Airflow.
• Expertise in distributed data processing and query engines, including tools such as:
• Trino
• Apache Spark
• Snowflake
• BigQuery
  

• Experience building large-scale infrastructure applications and writing maintainable code across multiple programming languages.
• Expertise with cloud platforms (AWS and/or GCP).
• Experience with containerisation and Infrastructure as Code, including:
• Docker
• Kubernetes
• Terraform
• Understanding of modern data architecture, with hands-on experience applying Data Mesh principles.
• Familiarity with notebook-based data science workflows.
• Experience with monitoring and observability tools such as:
• New Relic
• Grafana
• Prometheus
• ELK Stack