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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and maintaining production-grade data pipelines using Databricks, Delta Lake, and PySpark, while integrating APIs and webhooks with a focus on operational metrics and data governance. Proficient in implementing AI integrations and ensuring data lineage and compliance in regulated environments.
Highest-signal resume keywords
DatabricksDelta LakePySparkREST API DevelopmentAWS S3
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringBackend Integration EngineeringProduction Data PipelinesIncremental Data IngestionJira Cloud IntegrationAutomated TestingData GovernanceIdempotencyCI/CD AutomationOperational Documentation
Soft Skills
Advanced English Proficiency
Tools & Technologies
FastAPIFlaskGitCloudWatchDatadogNew Relic
Industry Keywords
FintechPayment PlatformsRegulated Data EnvironmentsSRE MetricsIncident Response
Tech Stack
Tools & technologiesAWSCloudFlaskPySparkPythonSparkSQLUnity
About the role
Key responsibilities & impact- Design and deliver the centralized Incident Management Platform (Vantage)
- Design, build, and maintain production-grade API and webhook integrations linking alerting systems, Jira Cloud/JSM, and internal services with the data platform
- Implement Jira AI-agent integrations featuring tool calling, structured outputs, auditable write-backs, and human-in-the-loop approval workflows
- Build robust, incremental data pipelines into Databricks using Delta Lake, PySpark, and SQL, ingesting from AWS S3
- Ensure pipeline idempotency, schema evolution, and reconciliation
- Design curated datasets powering SRE and operational metrics including MTTD, MTTR, incident coverage, and recurring-issue analysis
- Document data lineage, access controls, and retention policies
- Own testing suites, failure recovery/backfill procedures, and operational runbooks
- Ensure seamless handover to internal operations
- Bridge production backend systems, operational tools, and cloud data platforms
Requirements
What you’ll need- 5+ years in Data Engineering or Backend Integration Engineering, with a proven track record delivering production-grade data pipelines and services
- Hands-on mastery of Databricks, Delta Lake, and PySpark/Spark SQL in production environments, including jobs, workflows, medallion architectures, and incremental ingestion
- Demonstrable experience building and maintaining production REST APIs, webhooks, and lightweight backend services in Python, including FastAPI or Flask
- Experience with authentication, retries, rate-limiting, and idempotency
- Hands-on experience with core AWS services, primarily S3 and IAM, for secure storage and data ingestion
- Practical experience integrating LLMs/AI agents into real workflows, including human-in-the-loop validation, tool calling, and full audit logging
- Strong background in Git, CI/CD automation, automated unit/integration testing, and operational documentation/runbooks
- Advanced professional English proficiency, written and spoken
- 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 such as MTTR and MTTD and observability tools such as CloudWatch, Datadog, or New Relic
- Background in fintech, payment platforms, or regulated data environments
Benefits
Comp & perks- 100% remote
- Strategic, high-visibility role within a modern engineering culture
- Collaborative international team with strong technical leadership
- Career development and growth opportunities within Coderio
- Fair compensation
- Inclusive and challenging environment with real growth opportunities
