AI Summary
Design and operate hybrid data infrastructure, build high-performance ingestion pipelines, and implement data governance and observability.
Key Highlights
Design and operate hybrid data infrastructure across on-prem and cloud
Build high-performance ingestion pipelines for real-time and batch market data
Implement strong data governance, observability, and access patterns
Technical Skills Required
Benefits & Perks
Fully remote potential
Permanent or contract options
Job Description
🚀 Data Infrastructure Engineer | Hybrid (Fully remote potential) | High-Impact Role
Permanent or Contract
About the Opportunity
We’re looking for a Data Infrastructure Engineer to help build and maintain the data platform. If you enjoy solving hard performance problems, designing scalable systems, and working with high-volume data, this role offers a rare chance to make a direct, measurable impact.
What You’ll Be Working On
- Designing and operating hybrid data infrastructure across on-prem and cloud
- Building high-performance ingestion pipelines for real-time and batch market data
- Integrating data from internal systems and external vendors
- Implementing strong data governance, observability, and access patterns
- Automating deployments and infrastructure using modern DevOps & IaC tools
- Supporting critical production systems, including occasional after-hours cover
- Improving monitoring, alerting, and system reliability end-to-end
What We’re Looking For
- Degree in Maths, Engineering, Computer Science, or equivalent experience
- Strong background in distributed systems, object storage (e.g., S3), columnar formats, and streaming tech (Kafka)
- Linux, networking, and performance tuning expertise
- Cloud experience (AWS or GCP)
- Proficiency in Python, Go, or Java
- Solid SQL + data modelling foundations
- Kubernetes, Docker, and IaC experience
- Familiarity with orchestration tools like Airflow or Dagster
- Clear communicator with a passion for learning and problem-solving
- Knowledge of time-series/tick data, schema evolution, data versioning
- Experience in small, agile engineering teams
- Prometheus/Grafana or other observability tooling
- Exposure to Delta Lake, Iceberg, or Lakehouse architectures