Software Engineer (Data)

PRYPCO; Dubai; On-site; AED 240,000 - 420,000; Full time

Job summary

PRYPCO is seeking a Software Engineer (Data) to design and operate a reliable data platform that supports decision-making across the company. You will own end-to-end problems from architecture to automation and work closely with product, engineering, and data science teams.

You will design, implement, and maintain scalable ETL pipelines, establish data standards, and help users via dashboards and internal tools. A strong background in Python, SQL, and Airflow is required.

Qualifications

• 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 Trino, Apache Spark, Snowflake, and BigQuery.

Responsibilities

• Design, build, and maintain efficient, reliable data platforms, streamlining end-to-end data pipelines and automating manual workflows.
• Partner with cross-functional teams 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 organization-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.

Skills

Python

SQL

Unix shell scripting

Agile engineering practices

TDD

refactoring

CI/CD

XP

data-driven decisions

Education

Bachelor's or Master's in Computer Science

Tools

Apache Airflow

Trino

Apache Spark

Snowflake

BigQuery

Docker

Kubernetes

Terraform

Job description

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 organization-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:
  • 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
  • KubernetesTerraform
• 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