Senior Data & Integration Engineer – Incident Management Platform
New
C
CoderioIncident management
Listing location: Buenos Aires / Brasil / Uruguay; Workplace type: RemoteContractSenior
Salary not disclosed
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Job Details
- Languages
- Advanced professional English proficiency (written and spoken)
- Experience
- 5+ years in Data Engineering or Backend Integration Engineering
- Required Skills
- PythonRESTful APIsDatabricksPySpark
Requirements
- Have 5+ years of experience in Data Engineering or Backend Integration Engineering.
- Have a proven track record delivering production-grade data pipelines and services.
- Bring production experience with Databricks, Delta Lake, and PySpark/Spark SQL, including jobs, workflows, medallion architectures, and incremental ingestion.
- Build and maintain production REST APIs, webhooks, and lightweight backend services using Python, FastAPI, or Flask.
- Implement authentication, retries, rate-limiting, and idempotency in backend services and integrations.
- Have hands-on experience with AWS services, primarily S3 and IAM, for secure storage and data ingestion.
- Have practical experience integrating LLMs or AI agents into workflows, including human-in-the-loop validation, tool calling, and full audit logging.
- Have a strong background in Git, CI/CD automation, automated unit and integration testing, and operational documentation or runbooks.
- Have advanced professional English proficiency, written and spoken, for daily collaboration with multicultural, globally distributed teams.
- Jira Cloud or Jira Service Management API and webhook integration experience is a plus.
- Experience with data governance tools, Unity Catalog, row/column masking, or PII protection is a plus.
- Familiarity with SRE or incident-response metrics and observability tools such as CloudWatch, Datadog, or New Relic is a plus.
Responsibilities
- Design, build, and maintain production-grade API and webhook integrations connecting alerting systems, Jira Cloud/JSM, and internal services to the data platform.
- Implement Jira AI-agent integrations with tool calling, structured outputs, auditable write-backs, and human-in-the-loop approval workflows.
- Build incremental Databricks pipelines ingesting from AWS S3, with idempotency, schema evolution, and reconciliation.
- Design curated incident datasets for SRE and operational metrics, including MTTD, MTTR, incident coverage, and recurring-issue analysis.
- Document data lineage, access controls, and retention policies for incident data products.
- Own testing suites, failure recovery and backfill procedures, and operational runbooks for handover to internal operations.
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