SRE/Support Engineer
POSITION SUMMARY
- We are seeking a highly skilled DevOps / Site Reliability Engineer (SRE) with strong expertise in Market Data platforms, Python development, production application support, and DevOps tooling. This role is critical to ensuring the reliability, availability, performance, and data quality of market and investment data pipelines. The ideal candidate will combine hands-on production support, incident management, automation, and market data operations
POSITION RESPONSIBILITIES
- Python - Strong experience developing production-ready scripts for data orchestration, data processing, monitoring automation, log parsing, alerting, and incident remediation tools
- SQL / Oracle- Advanced ability to write complex queries for data validation, reconciliation, root cause analysis, and troubleshooting delayed, missing, or incorrect datasets • Data Flow & Pipeline Fundamentals - Solid understanding of end-to-end data pipelines,
- dependencies, data lineage, SLAs, critical path analysis, job failure triage, and data reprocessing
- GitLab - Hands-on experience with version control, repository management, and CI/CD pipelines for deploying automation, monitoring, and operational workflows
- Market Data Knowledge - Familiarity with market data delivery mechanisms such as file drops, SFTP, APIs, and streaming feeds. Experience validating pricing data, reference data, and corporate actions
- Market Data Vendor Platforms - Experience supporting and optimizing ingestion platforms using
- third-party data providers such as Bloomberg, Refinitiv, and other API-based vendors
- AWS Core Services - Working knowledge of S3, Lambda, Step Functions, and IAM for secure, event-driven data processing and workflow orchestration
EXPERIENCE AND REQUIRED SKILL SETS
- 1.Incident Resolution & Production Support
- Investigate and resolve job failures, delayed or missing data, application issues, infrastructure
- problems, and vendor feed disruptions
- Coordinate with internal teams and external data vendors to restore services quickly and minimize business impact
- 2. Data Quality & Validation
- Validate, reconcile, and analyse market and investment data using SQL
- Identify root causes of data anomalies before downstream consumption
- 3. Monitoring & Observability
- Design, implement, and maintain dashboards and alerts using Datadog, Splunk, and AWS services
- Automate health checks and proactive monitoring for data pipelines and applications
- 4. Operational Documentation & Runbooks
- Create and maintain accurate runbooks, workflows, and operational documentation Capture post-incident learnings and drive preventive improvements
- 5. Stakeholder & Vendor Collaboration
- Partner with business users, data engineering teams, and market data vendors to ensure smooth data delivery and timely issue resolution
- 6. Data Workflow Reliability
- Monitor pipeline health, enforce SLAs, and ensure consistent end-to-end data flow
- Support production data pipelines and investment data applications
- 7. Continuous Improvement
- Identify opportunities to enhance automation, monitoring, and operational efficiency
- Reduce manual intervention and improve overall system reliability
- 8. Market Data Integration Support
- Manage and troubleshoot third-party data feeds (SFTP, file drops, APIs)
- Ensure data accuracy, completeness, and uninterrupted ingestion