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Mrsool

On-demand delivery platform with P2P model

Data Engineer 2

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in IndiaRemote

About the Job

Requirements

  • At least 4 years of hands-on experience designing and building scalable data platforms, data lakes, and data warehouses.
  • Strong proficiency in Spark, Scala, Python, and SQL, including production-grade data pipelines and distributed data processing applications.
  • Hands-on experience with Apache Spark and understanding of distributed data processing, performance tuning, and optimization.
  • Experience building batch and streaming data pipelines using Kafka, CDC/Maxwell, or similar event-driven architectures.
  • Understanding of modern data lake architectures, including Medallion Architecture, data modeling, partitioning, and storage optimization.
  • Experience with cloud-native data platforms and technologies such as Amazon S3, BigQuery, and Trino or similar analytics engines.
  • Experience designing dimensional models and star schemas, and building reliable data marts for analytics and business intelligence.
  • Hands-on experience with dbt, including reusable models, automated testing, and documentation.
  • Knowledge of data quality, observability, lineage, and engineering best practices for reliable and maintainable data products.
  • Experience optimizing large-scale data pipelines, SQL queries, and distributed processing jobs for performance, scalability, and cost efficiency.
  • Familiarity with CI/CD, Git-based development workflows, infrastructure automation, and modern software engineering best practices.
  • Ability to independently own projects from design through production.
  • Experience collaborating across Product, Engineering, Analytics, and Business teams.

Responsibilities

  • Design, build, and maintain scalable batch and real-time data pipelines using Maxwell, Kafka, Spark, and dbt for analytics and business-critical applications.
  • Develop and optimize data models using Medallion Architecture (Bronze, Silver, Gold) to create reliable, reusable, and high-quality datasets.
  • Build and maintain cloud-native data platforms using S3, Spark, Trino, and BigQuery, ensuring scalability, reliability, and cost efficiency.
  • Design data ingestion frameworks using CDC (Maxwell), Kafka, and event-driven architectures for near-real-time data processing.
  • Create, optimize, and maintain data warehouses and data marts for fast, reliable reporting and self-service analytics.
  • Collaborate with Product Managers, Data Analysts, Backend Engineers, and business stakeholders to translate business requirements into scalable data solutions.
  • Develop reusable dbt models, testing frameworks, and documentation to improve data quality, governance, and developer productivity.
  • Optimize Spark jobs, Trino queries, and storage layouts for performance, reliability, and cost efficiency.
  • Own critical data pipelines end to end, ensuring high availability, monitoring, SLA adherence, and proactive incident resolution.
  • Develop reusable frameworks, automation, CI/CD pipelines, and engineering best practices to enhance the core data platform.
  • Ensure data quality through validation, monitoring, lineage, and observability, and implement security and governance best practices.
  • Deliver trusted datasets, semantic models, and Metabase dashboards to enable analytics teams and support decision-making.

About the Company

Mrsool

On-demand delivery platform with P2P model

Mrsool operates an on-demand delivery marketplace in Saudi Arabia that connects customers with couriers. Users describe the service they need in a chat, and available couriers bid their price to fulfill the request, after which the user picks a courier to complete the job. This bid-based, chat-driven model creates a scalable, person-to-person marketplace that spreads across cities and users. The goal is to grow a large, self-regulating network that efficiently matches buyers with couriers through simple chat interactions.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Riyadh, Saudi Arabia
Founded
2015

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