Software Engineer

• Design, develop, and maintain scalable data pipelines on Google Cloud Platform (GCP)
• Optimize and automate data workflows using Dataproc, BigQuery, Dataflow, Cloud Storage, and Pub/Sub
• Build and maintain ETL processes for data ingestion, transformation, and loading into data warehouses
• Ensure the reliability and performance of data pipelines by implementing Apache Airflow for orchestration
• Collaborate with stakeholders to gather and translate requirements into technical solutions
• Work on multiple data warehousing projects, applying a thorough understanding of concepts such as dimensions, facts, and slowly changing dimensions (SCDs)
• Develop scripts and applications in Python and PySpark to handle large-scale data processing tasks
• Write optimized SQL queries for data analysis and transformations
• Use GitHub, Jenkins, Terraform, and Ansible to deploy and manage code in production
• Troubleshoot and resolve issues related to data pipelines, ensuring high availability and scalability.

• Cloud Expertise: Hands-on experience with GCP services like Dataproc, BigQuery, Dataflow, Cloud Storage, and Pub/Sub
• Multi-cloud knowledge (e.g., AWS, Azure) is a plus
• Programming & Tools: Strong skills in Python, PySpark, and SQL for data processing and analysis
• Experience with Apache Airflow for workflow orchestration
• Data Warehousing: Clear understanding of dimensions, facts, SCDs, and other core data warehousing concepts
• Proven experience working on multiple data warehousing projects
• DevOps & Deployment Tools: Experience working with GitHub, Jenkins, Terraform, and Ansible for CI/CD processes
• General Skills: Strong problem-solving and analytical skills
• Excellent communication and stakeholder management abilities
• Ability to work independently and as part of a team.

Multi-cloud knowledge (e.g., AWS, Azure) is a plus.

• Continuous professional development
• Flexible working
• Opportunities for growth
• Inclusive and diverse environment.