Role: Data EngineerLocation: Egypt, Uzbekistan, and Pakistan (Remote)Work Week: Sunday – ThursdayWork Timings: 9:00 AM – 6:00 PM (Saudi Arabian Time Zone)Overview:We’re seeking a Data Engineer to design, build, and maintain the data infrastructure that underpins our analytics, ML models, and decision-making processes. You’ll be responsible for building scalable data pipelines, integrating diverse data sources, and ensuring data quality, reliability, and accessibility across the organization. Working closely with data scientists, analysts, and product teams, you’ll enable data-driven insights while optimizing for performance and scalability. This is a great opportunity to have a direct impact on how data is leveraged across a fast-growing company.Role & Responsibilities:Data Pipeline Development & Optimization:Design, build, and maintain scalable and reliable data pipelines to support analytics, ML models, and business reportingCollaborate with data scientists and analysts to ensure data is available, clean, and optimized for downstream useImplement data quality checks, monitoring, and validation processesData Architecture & Integration:Work with cross-functional teams to design efficient ETL/ELT workflows using modern data toolsIntegrate data from multiple sources (databases, APIs, third-party tools) into centralized storage solutions (data lakes/warehouses)Support cloud-based infrastructure for data storage and retrievalPerformance & Scalability:Monitor, troubleshoot, and optimize existing data pipelines to handle large-scale, real-time data flowsImplement best practices for query optimization and cost-efficient data storageEnsure data is available and accessible for business-critical operationsCollaboration & Documentation:Partner with product, engineering, and business stakeholders to understand data requirementsDocument data workflows, schemas, and best practicesSupport a culture of data reliability, governance, and securityRequirements:Proficiency in Python and SQL for data engineering tasksStrong understanding of ETL/ELT processes, data warehousing, and data modelingHands-on experience with cloud platforms (AWS, GCP, or Azure) and data storage solutions (BigQuery, Redshift, Snowflake, etc.)Familiarity with data orchestration tools Airflow, Airbyte is a mustExperience with containerization & deployment tools (Docker, Kubernetes) is a plusKnowledge of data governance, security, and best practices for handling sensitive dataFamiliarity to work with Git and GitHubDataform is a mustStrong skills in eliciting requirements from cross-functional stakeholders and translating them into actionable data engineering tasksExperience:2+ years in data engineering, building and maintaining data pipelines2+ years in SQL and Python development for production environmentsExperience working in fast-growing startup environments is a plusExposure to real-time data processing frameworks (Kafka, Spark, Flink) is a plusWe may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.