<h2><strong>The Wow</strong></h2> <p>This role is dedicated to the operational maintenance, governance, and delivery lifecycle of data assets. Unlike infrastructure-focused roles, the DataOps Engineer is responsible for user access provisioning, data platform permission management, deployment releases of analytical pipelines, and service observability (monitoring/alerting) to guarantee data availability and compliance without managing foundational cloud or network architecture.</p> <p>This role involves active monitoring, incident resolution, design incident prevention plan and engagement with data requests while continuously improving our data processes and systems, providing essential support that ensures optimal data quality.</p> <p> </p> <h2><strong>A taster of what you will be involved with: </strong></h2> <ul> <li>Access & Provisioning: Manage and audit Service Accounts, <strong>AWS IAM</strong> policies for data pipelines, and Role-Based Access Control (RBAC) schemas and Role & Permission management on <strong>Snowflake</strong>.</li> <li>Release Management: Execute and automate deployment releases for data pipeline codebases, orchestration logic and database schemas.</li> <li>Application Observability: Configure, monitor, and optimize pipeline alerting thresholds in <strong>Amazon CloudWatch</strong> and <strong>Coralogix</strong> to log task execution failures and data delivery delays.</li> <li>Application Orchestration: Manage workflows, task schedules, and environment permissions using <strong>Apache Airflow.</strong></li> <li>Incident Prevention: Actively design and implement preventive operations strategies, analysing system trends, pipeline bottlenecks, and job failures to eliminate systemic risks before SLA breaches occur.</li> <li>Advanced Monitoring & Alerting Engineering: Formulate and maintain sophisticated observability patterns, building real-time dashboards and threshold-based notification alerts inside <strong>Coralogix</strong> to flag delays, capacity exhaustion, or anomalies.</li> <li>Data Integrity & First-Line Response: Perform root-cause analysis on runtime pipeline anomalies and complex data flow errors, collaborating across analytics engineering teams to design permanent, scalable operational remediation.</li> <li>Perform rigorous investigations into data quality, identifying discrepancies and implementing corrective actions in collaboration with other teams.</li> <li>Collaborate on data engineering initiatives, focusing on the enhancement of existing processes and the development of new solutions to improve overall data workflow.</li> <li>Engage in incident monitoring and resolution, escalating more complex issues to second line support as necessary.</li> <li>Resource Optimization: Monitor query runtimes and compute consumption metrics to identify underutilized resources, proposing optimizations to maintain technical excellence and cost-efficiency.</li> <li>Manage incidents and perform on-call duties on related Technologies required at the Role.</li> <li><strong>Drive AI-powered innovation in Data Operations: </strong>Proactively identify opportunities to leverage AI, intelligent agents and automation to streamline operations, accelerate incident investigations and improve platform reliability. Experiment with emerging technologies and turn promising ideas into practical, impactful solutions.</li> </ul> <p> </p> <h2><strong>What we are looking for</strong></h2> <p>Must haves: <br><br></p> <ul> <li>Good experience configuring security structures, service integration privileges, and RBAC governance within enterprise data layers (e.g., <strong>Snowflake</strong> and <strong>AWS IAM</strong>).</li> <li>Proven expertise managing, deploying workflows, and debugging task execution failures in <strong>Apache Airflow.</strong></li> <li>Advanced skill in engineering cloud monitoring rules, logging metrics, and automated alert structures using <strong>Amazon CloudWatch and Coralogix.</strong></li> <li>High proficiency in writing complex SQL queries for dataset analysis and metadata tracking.</li> <li>Strong scripting capability in Python or shell environments to automate operational checklists, administrative tasks, and compliance auditing.</li> </ul> <p><br>Nice to have: </p> <ul> <li>Familiarity with broader modern data environments (AWS Glue, S3, Athena and Redshift).</li> <li>Exposure to data observability concepts and data contract mechanisms.</li> <li>Good Data Analysis experience to identify trends and track Data Quality issues.</li> <li>Excellent verbal and written English Communication skills.</li> <li>Strong interpersonal and communication skills with a customer-centric mindset; ability to build positive relationships with internal clients (data engineers, analysts, and business stakeholders) and translate complex technical operation issues into clear, actionable updates.</li> <li>Strong self-learning mindset: a highly proactive professional driven to explore new technologies, documentation, and industry best practices independently to continuously evolve their skill set.</li> <li>Able to set priorities, anticipate risks, and multitask under pressure.</li> <li>Proficiency in SQL for querying and managing datasets.</li> <li>Experience with scripting languages to automate and streamline ta