Senior Data Platform Engineer

Position Summary:

Avathon's Industrial AI Suite is the world's leading AI enabled SaaS platform that provides asset performance management and prescriptive analytics software to ever growing Aviation, Manufacturing, Mining, Renewable and Oil & gas energy power plants by combining the power of machine learning, big data, and deep domain expertise. Our Data Engineering and Science platform works across multiple capital intensive industrial asset types to offer insights to our customers.

Join us in developing and applying cutting-edge Enterprise Data Engineering solutions for commercial and industrial AI SaaS applications. We are looking for candidates with strong expertise in large scale Data Engineering, building scalable ETL pipelines to enable our AI enabled Saas Asset Performance Management. As a Senior Data platform Engineer you will be working closely with team members across domains with deep technical skills and Industrial AI domain.

What you will do:

• Work on engineering projects to design, construct, install, test and maintain highly scalable data management systems (data lakes, warehouses, pipelines) to ensure secure, efficient data flow and accessibility for analytics and AI/ML
• Building robust ETL pipelines and automating data workflows. Focus on automating data management, implementing DevOps principles (CI/CD, monitoring), and collaborating on data architecture.
• Utilise Key tools include Python, SQL, Cloud platforms (AWS/Azure/GCP), Kafka, Spark, and Docker.
• Developing and maintaining scalable ETL and MLOps pipelines and workflows.
• Enforcing data quality rules to ensure consistency, completeness, and accuracy across ETL processes.
• Designing, constructing, testing, and maintaining highly scalable data management systems.
• Mentoring a team of Data Analysts, Data Engineers, and Data Quality Specialists.
• Fostering a culture of continuous learning, collaboration, and data-driven decision-making.

You'll have:

• Excellent programming skills in Python, along with deep expertise in relational databases (MSSQL/MySQL/Postgres).
• 5+ years of hands-on experience in data engineering with a solid foundation in architecture principles.
• 1+ years of leadership or mentorship experience of data teams.
• Strong understanding of serverless architectures and building scalable ETL pipelines.
• Effective communication and leadership skills, capable of driving projects to completion.
• People and project management experience is a plus.

It would be great if you had:

• Experience in Industrial Engineering Systems like IoT time series data or even old legacy systems e.g. PLC, SCADA systems.
• Experience with cloud-native tools, particularly AWS or GCP.
• Willingness to adopt new technologies to enhance data quality and ETL processes.
• Hands-on experience in DevOps, focusing on cloud-native technologies.
• Expertise in debugging and troubleshooting ETL pipelines, data transformations, and integrity issues.

Other requirements:

This is 5 days onsite work week schedule

A design/ coding challenge is a prerequisite for this position.