Software Engineer (Data)

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. Requirements • 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 Nice to Have • 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