11 hours ago
Cairo, EgyptEntry Level
Responsibilities
- Design, build, and deploy cloud-native data pipelines and data solutions on platforms such as GCP and AWS.
- Develop ingestion pipelines from marketing, advertising, and CRM data sources into cloud data warehouses.
- Implement data models using dbt or Dataform to create analytics-ready datasets for reporting, measurement, and machine learning use cases.
- Write performant SQL transformations and serve large datasets in BigQuery, Snowflake, Redshift, or Databricks.
- Automate API authentication and ETL/ELT processes for cross-cloud data integration.
- Deploy and orchestrate pipelines using tools such as Cloud Workflows and dbt Cloud.
- Apply GenAI tools to engineering workflows and relevant client-facing data solutions.
- Contribute to data quality, documentation, deployment practices, and scalable pipeline development.
- Communicate technical concepts and solutions to technical and non-technical stakeholders, including clients.
Requirements
- Bachelor's or master's degree in a quantitative or technical subject such as Computer Science, Software Engineering, Data Engineering, or Information Systems.
- At least 1 year of experience in data engineering, analytics engineering, or a related field.
- Familiarity with designing and deploying cloud solutions on GCP or AWS.
- An associate cloud certification such as GCP Associate Cloud Engineer, GCP Professional Data Engineer, AWS Solutions Architect Associate, or equivalent.
- Strong proficiency in SQL and Python.
- Understanding of data warehousing, ETL/ELT concepts, and modern data-stack tools such as dbt, BigQuery, and Snowflake.
- Understanding of APIs, including API keys and OAuth authentication.
- Familiarity with cloud data services such as Cloud Functions, Cloud Run, Cloud Storage, Pub/Sub, Lambda, S3, and SNS/SQS.
- Awareness of GenAI tools such as Claude Code, Cursor, and Copilot.
- Fluent written and spoken English, strong analytical and problem-solving skills, and the ability to work independently and collaboratively.
- Preferred qualifications include professional cloud certifications, agency or consultancy experience, marketing analytics experience, DataOps and version-control familiarity, paid-media and social-data experience, BI-tool experience, and exposure to server-side tagging or customer data platforms.
Benefits
- Hybrid work arrangement, as indicated by the #LI-Hybrid designation.
- Opportunity to collaborate across the EMEA and MENA regions with analytics, strategy, and data science teams.
- Inclusive, equal-opportunity work environment focused on diversity, equity, and inclusion.
Tech Stack
Amazon RedshiftAWSAzureDatabricksdbtGitHub ActionsGoogle BigQueryGoogle Cloud PlatformLooker StudioPythonSnowflakeSQL
Categories
Data Engineering
About Monks
Monks combines an extraordinary range of global marketing and technology services to accelerate business possibilities and redefine how brands and businesses interact with the world. It delivers unfettered content production, scaled experiences, enterprise-grade technology and data science fueled by AI to help the world’s trailblazing companies outmaneuver and outpace their competition.