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Job Level
About the role
- Implement and maintain scalable environments with a focus on observability, automation, and reliability.
- Manage data infrastructure in AWS, with emphasis on Lake Formation, Glue Data Catalog, EMR, DynamoDB, and SageMaker.
- Support and evolve pipelines in Databricks and distributed processing environments.
- Define and monitor performance and availability metrics.
- Participate in critical incidents (War Rooms), conduct post-mortems, and drive continuous improvement.
- Collaborate with engineering, data, and product teams to ensure safe and efficient deliveries.
Requirements
- Strong experience as an SRE or DevOps engineer in data environments.
- Proficiency with observability tools (Datadog, Splunk, Prometheus).
- Advanced knowledge of AWS (Lake Formation, Glue, EMR, DynamoDB, SageMaker).
- Experience with Databricks, Apache Spark, and Data Lake architectures.
- Hands-on experience with IaC (Terraform, CloudFormation) and CI/CD.
- Knowledge of SQL and NoSQL databases.
- Familiarity with event-driven architectures and streaming technologies (Kafka, Kinesis, SQS/SNS).
- Experience in the agribusiness sector or with rural credit data.
- AWS or Databricks certifications.
- Knowledge of information security best practices in data environments.
Benefits
- Competitive compensation based on experience
- Opportunities for career growth and participation in strategic projects
- Dynamic and challenging work environment
- Opportunity to work at a rapidly growing company in the market.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
SREDevOpsobservabilityAWSLake FormationGlueEMRDynamoDBSageMakerDatabricks
Soft Skills
collaborationcontinuous improvementincident management
Certifications
AWS certificationDatabricks certification