At Aevi, we're not just a team; we're a vibrant, global community, committed to shaking up the payments industry. Our culture is all about innovation, creativity, and a passion for pushing boundaries. We’re thrilled to welcome new Aevi’ators who vibe with our values and mission and are ready to join us on our journey of transformation and growth.
As a Data Platform Engineer at Aevi, your primary responsibility is to make the data platform reliable, observable, and easy to operate by the whole team. This role is not about delivering one-off pipelines or dashboards. It is about strengthening platform foundations so data products can scale safely, remain trustworthy, and do not depend on individual experts.
Key responsibilities:
Improve reliability and operational stability of the Data Platform on AWS
Strengthen monitoring, alerting, and visibility across data pipelines and datasets
Simplify and standardize data pipelines so they can be operated by any team member
Automate deployments and reduce manual operational steps
Reduce single-person dependency through documentation, ownership, and runbooks
Support and evolve the Lakehouse architecture (Iceberg, Athena, QuickSight)
Design, operate, and improve data pipelines supporting both batch and near-real-time processing
Collaborate with Data Engineers, Analysts, and Architects to enforce platform standards
Skills, Qualifications & Experience:
Software Engineering (Required)
Strong programming skills to build and maintain data pipelines, automation, and tooling
Experience writing production-grade, testable, and maintainable code
Comfortable debugging complex systems and improving existing codebases
Experience with CI/CD, version control, and code reviews
Cloud & Platform Engineering (Required)
Strong experience with AWS (other clouds is a plus)
Hands-on experience with Infrastructure as Code (Terraform)
Experience with deployment automation and cloud-native monitoring
Data Platform Technologies (Required)
Experience with batch data processing in data lake or lakehouse architectures
Practical understanding of near-real-time / streaming data processing and when it is appropriate
Familiarity with Iceberg, Parquet, Athena, Presto/Trino, or similar technologies
Experience with data orchestration and pipeline management
Distributed & Big Data Systems (Nice to Have)
Exposure to streaming platforms (Kafka, Kinesis, or similar)
Experience with batch processing frameworks (Spark or similar)
Experience with Airflow or similar orchestration tools
Familiarity with containerization (Docker, Kubernetes)
Aevi person:
An out of the box thinker
Diplomatic
Passionate
Cool under pressure
A multitasker
An excellent communicator
Analytical
Entrepreneurial
A self-starter
Technology embracer (lover)
Happy
A team player
“A can do” mentality
