The Technical Operations Engineer is responsible for supporting the performance, reliability, and visibility of the Medlytix Production System. This role serves as a hybrid technical function combining production monitoring, telemetry analysis, workflow orchestration support, and automation engineering. Working under the direction of the Director, this individual plays a critical role in maintaining operational health across distributed systems, data pipelines, and workflow orchestration environments. The position requires strong hands-on expertise with monitoring tools, telemetry platforms, cloud technologies, and data processing systems. The Technical Operations Engineer evaluates system behavior, investigates production issues, supports and maintains monitoring of production systems, and drives automation and reliability improvements. The ideal candidate is highly proficient in relevant technical tools and platforms, with the ability to effectively monitor, analyze, and improve production systems. This role also requires strong critical thinking and problem-solving skills to evaluate complex system behaviors, identify root causes, and implement effective solutions across interconnected systems. Responsibilities:Monitor systems, workflows, and data pipelines to ensure optimal performance, high data quality, and system reliabilityBuild and maintain monitoring dashboards, alerts, and observability frameworks using telemetry toolsAnalyze workflow performance metrics (latency, failures) and identify trends or anomaliesSupport workflow orchestration platforms (e.g., Airflow) to ensure successful job execution and dependency managementTroubleshoot workflow failures, data pipeline issues, and system disruptions across distributed environmentsPerform root cause analysis using logs, telemetry data, and execution history, and provide actionable recommendationsManage and respond to production incidents, including triage, escalation, and coordination with cross-functional teamsEnsure data quality and integrity by implementing validation checks and identifying anomalies earlyDevelop automation scripts and tools to reduce manual operational effort and improve efficiencyIdentify opportunities to improve system reliability, fault tolerance, and operational scalabilityCollaborate with Engineering, Product, and Data teams to resolve issues and enhance system performanceCommunicate technical findings clearly and contribute to operational reporting and dashboards Requirements:Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or related field, with 3+ years of experience in technical operations, data engineering, or business intelligenceStrong proficiency in SQL and experience with Python or scripting for troubleshooting, analysis, and automationHands-on experience with workflow orchestration tools (e.g., Airflow) and data pipelinesFamiliarity with cloud platforms (AWS preferred) and monitoring/observability tools (e.g., Datadog, CloudWatch)Proven ability to perform root cause analysis and troubleshoot complex issues across distributed systemsStrong critical thinking and problem-solving skills with the ability to quickly learn and apply new tools and technologiesEffective communication skills with the ability to translate technical findings into actionable insightsExposure to ML/AI concepts, tools, or operational use cases is a plus