Staff Data Reliability Engineer

Summary

The Data Reliability Engineering team is responsible for helping build and maintain data cloud-native services and products, our main responsibility is ensuring high standards of reliability, scalability, and security during the entire data lifecycle.

What you'll do

• Responsible for building, maintaining, and evolving cloud-native and containerized infrastructure dedicated to hosting and integrating data products and services
• Play a crucial role in increasing our platform maturity by supporting other squads and participating as a team player in multidisciplinary projects, with a primary focus on availability, security, and scalability
• This staff position requires an advanced understanding of systems design, cloud infrastructure, network, and databases or data-related technologies, also is expected previous experiences in complex technology adoptions are expected.

Minimum Qualifications

• Solid experience with Cloud Management (AWS preferable)
• Solid experience with Kubernetes Management and Containerized applications
• Experience with observability (Logging and Metrics, nice-to-have Tracing)
• Experience with Shell Script and Linux Management
• Experience with automation language like Python or other
• Experience with Streaming (Kafka, Kinesis, or similar)
• Experience with Network (Load Balancer, Reverse Proxy, Gateway, VPC, NAT, etc.)
• Knowledge in Databases: MySQL and Postgres
• Desirable knowledge in BigData
• Desirable experience with serverless such as Lambda or Google Functions
• Desirable experience with orchestration tools like Airflow
• Desirable knowledge of development and design patterns
• Desirable experience with NoSQL database.

Core Benefits

• Remote work
• Flexible hours
• Gympass
• Meal & Food vouchers
• Remote work financial support
• Life Insurance
• Medical and Dental Assistance
• Employee child care benefit: daycare
• Vidalink partnership
• Day off (Birthday)
• Support for studying languages
• 50% off AWS and GCP certifications

Technologies that we apply in our day

Engineering

• Java, Groovy and Go
• Automated Testing
• K6 (Load Testing) and Gremlin (Chaos Testing)
• SQL / NoSQL
• Git
• Rest APIs and streaming data
• Cloud (AWS and Google)
• Docker and Kubernetes
• Codefresh & ArgoCD
• Grafana & Honeycomb
• Jira / Confluence

Data

• AWS Services;
• Data Processing: Spark, Flink
• Python
• Airflow
• Relational databases (PostgreSQL and MySQL)

Platform Engineering

• AWS
• Codefresh
• ArgoCD
• Grafana & Honeycomb
• Kubernetes
• Terraform
• Go, Python, and Shell Script
• Prometheus
• Istio

Security

• SAST
• SCA
• IaC Scans