Senior Data & Integration Engineer Incident Management Platform

About Us

Coderio designs and delivers scalable digital solutions for global companies. We combine strong technical expertise with a product mindset to lead complex software initiatives end-to-end. We work with international clients, value autonomy and clear communication, and build long-term partnerships through technical excellence.

More information: http://coderio.com

We are looking for a Senior Data & Integration Engineer to design and deliver our new centralized Incident Management Platform (Vantage). In this high-impact role, you will bridge the gap between production backend systems, operational tools, and cloud data platforms. You will connect alerting tools, Jira, and LLM-powered AI agents directly into our Databricks lakehouse to turn incident lifecycles into reliable, auditable, and well-governed data products.

The contract will initially be for 3 months, with the possibility of being extended to 6 months. 

What You Can Expect (Responsibilities):

• 
  

  End-to-End System Integration: Design, build, and maintain production-grade API and webhook integrations linking alerting systems, Jira Cloud/JSM, and internal services with our data platform.

  
  


• 
  

  AI-Agent & Workflow Engineering: Implement Jira AI-agent integrations featuring tool calling, structured outputs, auditable write-backs, and human-in-the-loop approval workflows.

  
  


• 
  

  Lakehouse Pipeline Engineering: Build robust, incremental data pipelines into Databricks (Delta Lake, PySpark, SQL) ingesting from AWS S3, ensuring idempotency, schema evolution, and reconciliation.

  
  


• 
  

  Governed Incident Data Models: Design curated datasets powering critical SRE and operational metrics (MTTD, MTTR, incident coverage, recurring-issue analysis) with documented data lineage, access controls, and retention policies.

  
  


• 
  

  Testing, Recovery & Handover: Take full ownership of testing suites, failure recovery/backfill procedures, and operational runbooks to ensure seamless handover to internal operations.

  
  

Requirements:

• 
  

  Experience: 5+ years in Data Engineering or Backend Integration Engineering, with a proven track record delivering production-grade data pipelines and services.

  
  


• 
  

  Databricks & Lakehouse: Hands-on mastery of Databricks, Delta Lake, and PySpark/Spark SQL in production environments (jobs, workflows, medallion architectures, incremental ingestion).

  
  


• 
  

  APIs & Backend Services: Demonstrable experience building and maintaining production REST APIs, webhooks, and lightweight backend services in Python (FastAPI, Flask) with proper authentication, retries, rate-limiting, and idempotency.

  
  


• 
  

  AWS Foundation: Hands-on experience with core AWS services, primarily S3 and IAM, for secure storage and data ingestion.

  
  


• 
  

  AI & Agentic Controls: Practical experience integrating LLMs/AI agents into real workflows, specifically implementing human-in-the-loop validation, tool calling, and full audit logging.

  
  


• 
  

  Engineering Discipline: Strong background in Git, CI/CD automation, automated testing (unit/integration), and drafting clear operational documentation/runbooks.

  
  


• 
  

  English Proficiency: Advanced professional English proficiency (written and spoken) to collaborate daily with multicultural, globally distributed teams.

  
  

Nice to Have:

• 
  

  Direct integration experience with Jira Cloud / Jira Service Management APIs and Webhooks.

  
  


• 
  

  Experience implementing data governance tools (such as Databricks Unity Catalog, row/column masking, and PII protection).

  
  


• 
  

  Familiarity with SRE/incident response metrics (MTTR, MTTD) and observability tools (CloudWatch, Datadog, or New Relic).

  
  


• 
  

  Background in fintech, payment platforms, or regulated data environments.