Job Description
Roles & Responsibilities
Monitor operational workflows and system processes (data ingestion, post-ingestion, and UI delivery) to ensure smooth and uninterrupted service.
Monitor the health of our applications and troubleshoot by following provided runbooks or documentation.
Investigate and understand root causes for issues in business operations; develop and implement corrective actions
Log issues, delays, and anomalies accurately and escalate critical problems per internal protocols.
Respond to client queries promptly and professionally, ensuring resolution within defined timelines.
Work with clients and internal teams to provide timely solutions while ensuring compliance with company standards and regulations.
Deliver outputs accurately and within agreed SLAs, maintaining high reliability standards.
Collaborate with Engineering, Product, and Client Success teams to resolve incidents, align on expectations, and drive process improvements.
Maintain detailed records of incidents, client interactions, and operational metrics for reporting, audits, and analysis.
Identify recurring issues and contribute to the design of preventive measures and long-term solutions.
Use SQL, Shell scripting, and programming skills (python) as part of technical operations support.
Support automation and workflow improvements to increase operational efficiency.
Required Qualifications
5+ years of experience in operations, data engineering, or Production support roles.
Proven hands-on experience in querying and analyzing data, Advanced Excel, and My SQL.
Experience in Linux basics and Networking fundamentals.
Experience using cloud technologies such as AWS.
Strong analytical and troubleshooting skills.
Familiarity with workflow orchestration tools (Airflow), cloud infrastructure, and containerization (Kubernetes).
Strong communication, documentation, and cross-team collaboration skills.
Ability to work in a fast-paced, client-focused environment.
Proactive, detail-oriented, and committed to continuous improvement.
Preferred Qualifications
Experience working in Saa S, energy, or data-driven industries.
Experience with Datadog or similar health monitoring systems.
Experience in py Spark, data management, data integration, ETL, data quality and controls, data analysis, reporting, and testing.
Familiarity with UI-based client platforms and Excel API integrations.
Exposure to monitoring and alerting tools, including custom scripting.
Exposure to Git
Experience using Agile methodologies.
Experience working with Jira or other issue-tracking systems.
Monitor operational workflows and system processes (data ingestion, post-ingestion, and UI delivery) to ensure smooth and uninterrupted service.
Monitor the health of our applications and troubleshoot by following provided runbooks or documentation.
Investigate and understand root causes for issues in business operations; develop and implement corrective actions
Log issues, delays, and anomalies accurately and escalate critical problems per internal protocols.
Respond to client queries promptly and professionally, ensuring resolution within defined timelines.
Work with clients and internal teams to provide timely solutions while ensuring compliance with company standards and regulations.
Deliver outputs accurately and within agreed SLAs, maintaining high reliability standards.
Collaborate with Engineering, Product, and Client Success teams to resolve incidents, align on expectations, and drive process improvements.
Maintain detailed records of incidents, client interactions, and operational metrics for reporting, audits, and analysis.
Identify recurring issues and contribute to the design of preventive measures and long-term solutions.
Use SQL, Shell scripting, and programming skills (python) as part of technical operations support.
Support automation and workflow improvements to increase operational efficiency.
Required Qualifications
5+ years of experience in operations, data engineering, or Production support roles.
Proven hands-on experience in querying and analyzing data, Advanced Excel, and My SQL.
Experience in Linux basics and Networking fundamentals.
Experience using cloud technologies such as AWS.
Strong analytical and troubleshooting skills.
Familiarity with workflow orchestration tools (Airflow), cloud infrastructure, and containerization (Kubernetes).
Strong communication, documentation, and cross-team collaboration skills.
Ability to work in a fast-paced, client-focused environment.
Proactive, detail-oriented, and committed to continuous improvement.
Preferred Qualifications
Experience working in Saa S, energy, or data-driven industries.
Experience with Datadog or similar health monitoring systems.
Experience in py Spark, data management, data integration, ETL, data quality and controls, data analysis, reporting, and testing.
Familiarity with UI-based client platforms and Excel API integrations.
Exposure to monitoring and alerting tools, including custom scripting.
Exposure to Git
Experience using Agile methodologies.
Experience working with Jira or other issue-tracking systems.
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