About the Role
We are looking for a Data Platform Engineer to support the day-to-day stability, performance, and reliability of enterprise data platforms in production.
This role focuses on hands-on troubleshooting, operational support, and platform maintenance, working under the guidance of senior data engineers, architects, and SRE teams.
You will support data pipelines, data warehouses, analytics platforms, and selected AI/ML services, ensuring issues are resolved efficiently and systems operate reliably in a production environment.
Key Responsibilities
Production Support & Incident Handling
- Act as an advanced support engineer for Data Platform incidents escalated from L1
- Troubleshoot and resolve medium-complexity production issues
- Participate in incident response activities, including:
- Log analysis and diagnostics
- Root cause identification
- Minor code or configuration fixes
- Fix validation and post-fix monitoring
- Escalate complex or systemic issues to Engineering or Architecture teams with clear findings and evidence
- Assist in post-incident reviews and documentation
- Create and maintain operational handbooks, runbooks, and SOPs
- [Bonus] Develop monitoring, alerting, or process automation tools to improve operational efficiency
Platform Operations & Reliability
- Monitor health, performance, and availability of:
- Data pipelines and orchestration workflows
- Data warehouses and data lakes
- Analytics and reporting platforms
- Perform routine operational tasks, including:
- Job restarts and failure recovery
- Data quality checks and validations
- Query or pipeline performance tuning
- Operational and configuration-level fixes
- Support platform stability improvements by following and enhancing existing runbooks and SOPs
Troubleshooting & Support
- Investigate issues across:
- Batch and streaming data pipelines
- SQL queries and data models
- APIs and data platform services
- Assist with analysis of:
- Query performance degradation
- Data latency or freshness issues
- Cost anomalies or resource over-utilization
- Follow, update, and improve troubleshooting guides and operational documentation
Collaboration & Knowledge Sharing
- Work closely with:
- L1 support engineers
- SRE teams
- Delivery and project teams during solution handover
- Support project-to-operations transition and production acceptance activities
- Contribute to internal documentation and shared knowledge base
- Share recurring issues, patterns, and learnings with the wider engineering team
Required Skills & Experience
Core Requirements
- 2–4 years of experience in:
- Data engineering
- Data platform operations
- Cloud or analytics support roles
- Hands-on experience with:
- Cloud platforms (GCP / AWS / Azure)
- Data warehouses and data lakes
- Batch and/or streaming data pipelines
- Strong SQL skills for:
- Data validation
- Issue investigation
- Performance analysis
- Experience troubleshooting:
- Failed data jobs
- Pipeline errors
- Data inconsistencies
Platform & Technical Skills
- Familiarity with:
- Data orchestration and workflow tools
- API- and microservice-based platforms
- Logging, monitoring, and alerting tools
- Basic understanding of:
- Distributed systems concepts
- Cloud infrastructure components
Exposure to AI / Advanced Workloads (Nice to Have)
- Exposure to supporting:
- AI / ML pipelines
- GenAI or inference services
- Basic understanding of:
- AI job execution and dependencies
- Model inference latency considerations
- Data inputs and outputs for AI workloads
Nice to Have
- Experience with:
- Containerized or serverless workloads
- CI/CD pipelines for data platforms
- Awareness of:
- Cost monitoring or FinOps concepts
- IAM and access control in cloud environments
- Prior experience in:
- Managed services
- Customer-facing support or operations roles
Working Style & Mindset
- Hands-on and detail-oriented
- Comfortable working with operational processes and runbooks
- Calm and methodical during production incidents
- Willing to learn and grow into deeper platform and engineering responsibilities
- Clear and structured communicator when escalating issues