Data Support Engineer, L1/L2 & Data Pipelines
Overview
You will own L1/L2 support for mission-critical Data Pipelines in a $331bn energy trading environment. You'll ensure high availability and reliability of Datadog-monitored systems, collaborating with global teams across 40 offices. This role offers direct exposure to business operations and the latest data platform technologies, with an on-call rotation and after-hours support. You'll drive continuous improvement in support processes while working 5 days a week in Houston, TX.
What You'll Do10
- 1Triage and resolve incidents for Data Pipelines, ETL jobs, and real-time data feeds within SLA.
- 2Monitor pipeline health and performance using Datadog, Splunk, and Grafana, acting on alerts.
- 3Respond to user queries and service requests, maintaining high satisfaction and clear documentation.
- 4Escalate complex issues to L3 or development teams with detailed handoff notes.
- 5Execute routine operational tasks: digest failure notifications, vendor credential management, batch job monitoring, and data integrity checks.
- 6Collaborate with business users to clarify requirements and guide on data functionality.
- 7Update support documentation, knowledge bases, and runbooks after each incident.
- 8Identify recurring issues and contribute to root cause analysis and problem management.
- 9Support incident and change management processes aligned with ITIL best practices.
- 10Participate in on-call rotation and provide after-hours support as scheduled.
Requirements10
- 13+ years in application support within energy trading, financial services, or data-intensive industries.
- 2Solid grasp of L1/L2 support processes, incident management, and service desk operations.
- 3Experience supporting data warehouses, ETL pipelines, reporting tools, or real-time data feeds.
- 4Ability to read and write basic Python scripts for automated data quality checks.
- 5Proficiency in SQL for data investigation and troubleshooting.
- 6Familiarity with Linux/Unix and Windows operating systems.
- 7Experience with monitoring tools such as Datadog, Splunk, Grafana, or AppDynamics.
- 8Strong analytical and problem-solving skills, with the ability to prioritize under pressure.
- 9Excellent written and verbal communication skills for technical and non-technical stakeholders.
- 10Customer-focused mindset and ability to work effectively in a distributed, worldwide team.
Salary Insight
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