Data Engineer

Job not on LinkedIn

September 21

Apply Now

Receive Emails with Similar Jobs

Soum

WebsiteLinkedInAll Job Openings

Soum is on a mission to reimagine recommerce in the MENA region and beyond, building the most convenient, trustworthy, and transparent recommerce marketplace in the region.

11 - 50 employees

📋 Description

• Design, build, and maintain scalable and reliable data pipelines to support analytics, ML models, and business reporting. • Collaborate with data scientists and analysts to ensure data is available, clean, and optimized for downstream use. • Implement data quality checks, monitoring, and validation processes. • Work with cross-functional teams to design efficient ETL/ELT workflows using modern data tools. • Integrate data from multiple sources (databases, APIs, third-party tools) into centralized storage solutions (data lakes/warehouses). • Support cloud-based infrastructure for data storage and retrieval. • Monitor, troubleshoot, and optimize existing data pipelines to handle large-scale, real-time data flows. • Implement best practices for query optimization and cost-efficient data storage. • Ensure data is available and accessible for business-critical operations. • Partner with product, engineering, and business stakeholders to understand data requirements. • Document data workflows, schemas, and best practices. • Support a culture of data reliability, governance, and security.

🎯 Requirements

• Strong understanding of ETL/ELT processes, data warehousing, and data modeling. • Hands-on experience with cloud platforms (AWS, GCP, or Azure) and data storage solutions (BigQuery, Redshift, Snowflake, etc.). • Familiarity with data orchestration tools (Airflow, dbt, Prefect, or similar). • Experience with containerization & deployment tools (Docker, Kubernetes) is a plus. • Knowledge of data governance, security, and best practices for handling sensitive data. • 2+ years in data engineering, building and maintaining data pipelines. • 2+ years in SQL and Python development for production environments. • Experience working in fast-growing startup environments is a plus. • Exposure to real-time data processing frameworks (Kafka, Spark, Flink) is a plus.