Senior Data & Integration Engineer – Incident Management Platform
New
J
JobgetherIncident management
Based in BrazilContractSenior
Salary not disclosed
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Job Details
- Languages
- Advanced professional English proficiency, both written and spoken
- Experience
- At least 5 years of professional experience in Data Engineering, Backend Integration Engineering, or a closely related technical role.
- Required Skills
- PythonSQLFastAPIRESTful APIsDatabricksPySpark
Requirements
- At least 5 years of professional experience in Data Engineering, Backend Integration Engineering, or a closely related technical role.
- Production experience designing and maintaining data pipelines, backend services, and system integrations.
- Hands-on production expertise with Databricks, Delta Lake, and PySpark or Spark SQL.
- Experience with Databricks jobs, workflows, medallion architecture, and incremental data ingestion.
- Experience building REST APIs, webhooks, and lightweight backend services using Python frameworks such as FastAPI or Flask.
- Understanding of API authentication, retry mechanisms, rate limiting, error handling, and idempotency.
- Practical experience with AWS services, particularly Amazon S3 and IAM.
- Hands-on experience integrating LLMs or AI agents into business workflows.
- Understanding of agentic workflows, including tool calling, human-in-the-loop validation, structured outputs, and audit logging.
- Strong software engineering fundamentals, including Git, CI/CD automation, and automated unit and integration testing.
- Ability to develop technical documentation, operational procedures, and system recovery runbooks.
- Advanced professional English proficiency, written and spoken.
Responsibilities
- Design and maintain API and webhook integrations connecting alerting platforms, Jira Cloud, Jira Service Management, internal services, and centralized data infrastructure.
- Build AI-agent integrations in Jira workflows, including tool calling, structured outputs, auditable write-backs, and human-in-the-loop approvals.
- Develop data pipelines with Databricks, Delta Lake, PySpark, and SQL to ingest and process data from AWS S3 and integrated systems.
- Implement incremental ingestion, idempotent processing, schema evolution, and data reconciliation to support reliable pipelines.
- Design governed incident data models and curated datasets for SRE metrics, incident coverage, and recurring incident analysis.
- Establish data governance practices covering lineage, access controls, retention policies, and security.
- Develop testing strategies and automated test suites for integrations, pipelines, and AI-powered workflows.
- Implement failure recovery, backfills, and reconciliation procedures to maintain resilience and data consistency.
- Create operational documentation, technical specifications, and runbooks.
- Own technical deliverables through implementation, testing, deployment, and handover to internal operations teams.
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