Senior Data Engineer
Washmen.com
Office
Dubai
Full Time
Position OverviewWe're seeking a self-sufficient Senior Data Engineer to build and scale our data infrastructure supporting product, engineering and analytics team. You'll architect data pipelines, optimize our data platform, and ensure the teams have reliable, high-quality data to drive business decisions.This is a hands-on role for someone who can own the entire data engineering stack - from ingestion to transformation to orchestration. You'll work independently to solve complex data challenges and build scalable solutions.
Core Responsibilities
Data Pipeline Development & OptimizationDesign, build, and maintain scalable data pipelines using Spark and DatabricksDevelop ETL/ELT workflows to process large volumes of customer behavior dataOptimize Spark jobs for performance, cost efficiency, and reliabilityBuild real-time and batch data processing solutionsImplement data quality checks and monitoring throughout pipelinesEnsure data freshness and SLA compliance for analytics workloads
AWS Data InfrastructureArchitect and manage data infrastructure on AWS (S3, Glue, EMR, Redshift)Design and implement data lake architecture with proper partitioning and optimizationConfigure and optimize AWS Glue for ETL jobs and data catalogingShifting Glue jobs to Zero ETLImplement security best practices for data access and governanceMonitor and optimize cloud costs related to data infrastructure
Data Modeling & ArchitectureDesign and implement dimensional data models for analyticsBuild star/snowflake schemas optimized for analytical queriesCreate data marts for specific business domains (retention, campaigns, product)Ensure data model scalability and maintainabilityDocument data lineage, dependencies, and business logicImplement slowly changing dimensions and historical tracking
Orchestration & AutomationBuild and maintain workflow orchestration using Airflow or similar toolsImplement scheduling, monitoring, and alerting for data pipelinesCreate automated data quality validation frameworksDesign retry logic and error handling for production pipelinesBuild CI/CD pipelines for data workflowsAutomate infrastructure provisioning using Infrastructure as Code
Cross-Functional CollaborationPartner with Senior Data Analyst to understand analytics requirementsWork with Growth Director and team to enable data-driven decision makingSupport CRM Lead with data needs for campaign executionCollaborate with Product and Engineering on event tracking and instrumentationDocument technical specifications and best practices for the teamWork closely with all squads , establish data contracts with engineers to land data in a most optimal way.
Required Qualifications
Must-Have Technical SkillsApache Spark: Expert-level proficiency in PySpark/Spark SQL for large-scale data processing - this is non-negotiableDatabricks: Strong hands-on experience building and optimizing pipelines on Databricks platform - this is non-negotiableAWS: Deep knowledge of AWS data services (S3, Glue, EMR, Redshift, Athena) - this is non-negotiableData Modeling: Proven experience designing dimensional models and data warehouses - this is non-negotiableOrchestration: Strong experience with workflow orchestration tools (Airflow, Prefect, or similar) - this is non-negotiableSQL: Advanced SQL skills for complex queries and optimizationPython: Strong programming skills for data engineering tasks
Experience6-10 years in data engineering with focus on building scalable data platformsProven track record architecting and implementing data infrastructure from scratchExperience processing large volumes of event data (billions of records)Background in high-growth tech companies or consumer-facing productsExperience with mobile/web analytics data preferred
Technical RequirementsExpert in Apache Spark (PySpark and Spark SQL) with performance tuning experienceDeep hands-on experience with Databricks (clusters, jobs, notebooks, Delta Lake)Strong AWS expertise: S3, Glue, EMR, Redshift, Athena, Lambda, CloudWatchProficiency with orchestration tools: Airflow, Prefect, Step Functions, or similarAdvanced data modeling skills: dimensional modeling, normalization, denormalizationExperience with data formats: Parquet, Avro, ORC, Delta LakeVersion control with Git and CI/CD practicesInfrastructure as Code: Terraform, CloudFormation, or similarUnderstanding of data streaming technologies (Kafka, Kinesis) is a plus
Core CompetenciesSelf-sufficient: You figure things out independently without constant guidanceProblem solver: You diagnose and fix complex data pipeline issues autonomouslyPerformance-focused: You optimize for speed, cost, and reliabilityQuality-driven: You build robust, maintainable, and well-documented solutionsOwnership mindset: You take end-to-end responsibility for your workCollaborative: You work well with analysts and business stakeholders despite being independent
Nice-to-HaveDatabricks certifications (Data Engineer Associate/Professional)Experience with dbt for data transformationKnowledge of customer data platforms (Segment, mParticle, Rudderstack)Experience with event tracking platforms (Mixpanel, Amplitude)Familiarity with machine learning infrastructure and MLOpsExperience in MENA region or emerging marketsBackground in on-demand services, marketplaces, or subscription businessesKnowledge of real-time streaming architectures
What We OfferCompetitive salary based on experienceOwnership of critical data infrastructure and architecture decisionsWork with modern data stack and cutting-edge AWS technologiesDirect impact on business decisions through data platform improvementsComprehensive health benefits
Core Responsibilities
Data Pipeline Development & OptimizationDesign, build, and maintain scalable data pipelines using Spark and DatabricksDevelop ETL/ELT workflows to process large volumes of customer behavior dataOptimize Spark jobs for performance, cost efficiency, and reliabilityBuild real-time and batch data processing solutionsImplement data quality checks and monitoring throughout pipelinesEnsure data freshness and SLA compliance for analytics workloads
AWS Data InfrastructureArchitect and manage data infrastructure on AWS (S3, Glue, EMR, Redshift)Design and implement data lake architecture with proper partitioning and optimizationConfigure and optimize AWS Glue for ETL jobs and data catalogingShifting Glue jobs to Zero ETLImplement security best practices for data access and governanceMonitor and optimize cloud costs related to data infrastructure
Data Modeling & ArchitectureDesign and implement dimensional data models for analyticsBuild star/snowflake schemas optimized for analytical queriesCreate data marts for specific business domains (retention, campaigns, product)Ensure data model scalability and maintainabilityDocument data lineage, dependencies, and business logicImplement slowly changing dimensions and historical tracking
Orchestration & AutomationBuild and maintain workflow orchestration using Airflow or similar toolsImplement scheduling, monitoring, and alerting for data pipelinesCreate automated data quality validation frameworksDesign retry logic and error handling for production pipelinesBuild CI/CD pipelines for data workflowsAutomate infrastructure provisioning using Infrastructure as Code
Cross-Functional CollaborationPartner with Senior Data Analyst to understand analytics requirementsWork with Growth Director and team to enable data-driven decision makingSupport CRM Lead with data needs for campaign executionCollaborate with Product and Engineering on event tracking and instrumentationDocument technical specifications and best practices for the teamWork closely with all squads , establish data contracts with engineers to land data in a most optimal way.
Required Qualifications
Must-Have Technical SkillsApache Spark: Expert-level proficiency in PySpark/Spark SQL for large-scale data processing - this is non-negotiableDatabricks: Strong hands-on experience building and optimizing pipelines on Databricks platform - this is non-negotiableAWS: Deep knowledge of AWS data services (S3, Glue, EMR, Redshift, Athena) - this is non-negotiableData Modeling: Proven experience designing dimensional models and data warehouses - this is non-negotiableOrchestration: Strong experience with workflow orchestration tools (Airflow, Prefect, or similar) - this is non-negotiableSQL: Advanced SQL skills for complex queries and optimizationPython: Strong programming skills for data engineering tasks
Experience6-10 years in data engineering with focus on building scalable data platformsProven track record architecting and implementing data infrastructure from scratchExperience processing large volumes of event data (billions of records)Background in high-growth tech companies or consumer-facing productsExperience with mobile/web analytics data preferred
Technical RequirementsExpert in Apache Spark (PySpark and Spark SQL) with performance tuning experienceDeep hands-on experience with Databricks (clusters, jobs, notebooks, Delta Lake)Strong AWS expertise: S3, Glue, EMR, Redshift, Athena, Lambda, CloudWatchProficiency with orchestration tools: Airflow, Prefect, Step Functions, or similarAdvanced data modeling skills: dimensional modeling, normalization, denormalizationExperience with data formats: Parquet, Avro, ORC, Delta LakeVersion control with Git and CI/CD practicesInfrastructure as Code: Terraform, CloudFormation, or similarUnderstanding of data streaming technologies (Kafka, Kinesis) is a plus
Core CompetenciesSelf-sufficient: You figure things out independently without constant guidanceProblem solver: You diagnose and fix complex data pipeline issues autonomouslyPerformance-focused: You optimize for speed, cost, and reliabilityQuality-driven: You build robust, maintainable, and well-documented solutionsOwnership mindset: You take end-to-end responsibility for your workCollaborative: You work well with analysts and business stakeholders despite being independent
Nice-to-HaveDatabricks certifications (Data Engineer Associate/Professional)Experience with dbt for data transformationKnowledge of customer data platforms (Segment, mParticle, Rudderstack)Experience with event tracking platforms (Mixpanel, Amplitude)Familiarity with machine learning infrastructure and MLOpsExperience in MENA region or emerging marketsBackground in on-demand services, marketplaces, or subscription businessesKnowledge of real-time streaming architectures
What We OfferCompetitive salary based on experienceOwnership of critical data infrastructure and architecture decisionsWork with modern data stack and cutting-edge AWS technologiesDirect impact on business decisions through data platform improvementsComprehensive health benefits
Senior Data Engineer
Office
Dubai
Full Time
October 2, 2025