MRSOOL | مرسول

DevOps Engineer

• Collaborate with development teams to design and implement scalable infrastructure
• Design and implement automated deployment and testing pipelines
• Develop and maintain monitoring and alerting systems
• Troubleshoot and escalate production incidents to minimize downtime and improve reliability
• Continuously improve infrastructure and processes for scalability and efficiency
• Participate in and own on-call rotations to provide 24/7 application support
• Perform routine maintenance and upgrades
• Improve security posture and compliance with industry standards
• Communicate technical concepts to technical and non-technical stakeholders
• Mentor and coach junior engineers
• Stay current with site reliability engineering advancements and share knowledge
• Identify organizational enhancements and propose alternatives to optimize team structures and execution

Site Reliability Engineer II

Data Engineer

• Design, build, and maintain scalable batch and real-time data pipelines using Maxwell, Kafka, Spark, and dbt
• Develop and optimize data models following Medallion Architecture (Bronze, Silver, Gold)
• Build and maintain cloud-native data platforms using S3, Spark, Trino, and BigQuery
• Design data ingestion frameworks leveraging CDC (Maxwell), Kafka, and event-driven architectures
• Create, optimize, and maintain data warehouses and data marts
• Partner with Product Managers, Data Analysts, Backend Engineers, and Business stakeholders to translate requirements into data solutions
• Develop reusable dbt models, testing frameworks, and documentation
• Optimize Spark jobs, Trino queries, and storage layouts
• Own the lifecycle of critical data pipelines, including availability, monitoring, SLA adherence, and incident resolution
• Build reusable frameworks, automation, CI/CD pipelines, and engineering best practices for the core data platform
• Ensure data quality through validation, monitoring, lineage, and observability, while implementing security and governance practices
• Deliver trusted datasets, semantic models, and Metabase dashboards for analytics and decision-making

Data Engineer II

Backend Engineer

• Lead end-to-end project execution by driving RFCs, high-level and low-level design documents, and execution plans
• Design, build, and maintain highly concurrent, low-latency backend systems handling massive transactional throughput
• Influence technical decisions and project direction using Ruby on Rails, Go, and other backend technologies
• Write clean, performance-optimized, maintainable code
• Optimize database performance, query execution, and cache-layer strategies using PostgreSQL, Redis, and related technologies
• Safeguard data consistency across microservices
• Collaborate with product managers, designers, DevOps, and engineering squads on integrations and user experiences
• Mentor and coach junior and mid-level engineers
• Review complex pull requests
• Identify system bottlenecks and address root causes of infrastructure issues
• Champion automated testing, observability, tracing, metrics, and CI/CD automation
• Identify organizational improvements and propose technical alternatives
• Balance short-term feature delivery with long-term architectural stability

SDE III – Backend Engineer

Data Scientist

• Build and maintain ML and optimisation models across the quick-commerce stack, including supply-demand matching, dynamic and surge pricing, recommendations, ETA prediction, and marketplace optimisation
• Contribute to Butler's conversational ordering AI by modelling customer intent from text, voice, and images and mapping requests to fulfillable, well-priced orders
• Design and run A/B and quasi-experiments across pricing, matching, recommendations, and Butler
• Turn noisy marketplace data into actionable stakeholder decisions
• Engineer features from order events, courier traces, geospatial signals, pricing configurations, and conversational text/voice
• Own models through data pipelines, training, deployment, monitoring, and retraining
• Respond to model or configuration drift
• Collaborate with product managers, engineers, DevOps, operations, and other squads
• Help diagnose live issues such as mispriced brackets and elevated failure rates
• Monitor model and metric health and contribute to logging, observability, analysis, and deployment practices
• Identify improvements to measurement, modelling, and processes through incremental changes

Data Scientist II

• Design, build, and maintain scalable batch and real-time data pipelines using Maxwell, Kafka, Spark, and dbt
• Develop and optimize Bronze, Silver, and Gold data models using Medallion Architecture
• Build and maintain cloud-native data platforms using S3, Spark, Trino, and BigQuery
• Design data ingestion frameworks using CDC, Kafka, and event-driven architectures
• Create and maintain data warehouses and data marts for reporting and self-service analytics
• Translate business requirements into scalable data solutions with Product, Analytics, Engineering, and Business stakeholders
• Develop reusable dbt models, testing frameworks, and documentation
• Optimize Spark jobs, Trino queries, and storage layouts
• Own critical data pipeline lifecycles, monitoring, SLA adherence, and incident resolution
• Build reusable data-platform frameworks, automation, CI/CD pipelines, and engineering practices
• Ensure data quality through validation, monitoring, lineage, observability, security, and governance
• Deliver trusted datasets, semantic models, and Metabase dashboards for decision-making