Qureos

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Analytics Engineer

Cairo, Egypt

Design, build, and maintain trusted, scalable, and well-documented data models and pipelines using modern analytics engineering tools. This role ensures that analysts and business leaders can extract insights efficiently and reliably from clean data layers.

Responsibilities

  • Data Modeling & Transformation
  • Develop and maintain dbt models with standardized naming, structure, and robust documentation.
  • Create analytics-ready data marts by transforming raw data into clean, structured datasets.
  • Write modular, well-tested, and efficient SQL code to power modeling layers.
  • Data Pipeline Development
  • Build reliable and scalable data pipelines for ingestion, transformation, and validation.
  • Monitor and troubleshoot data pipeline performance, latency, and failures.
  • Cross-functional Collaboration
  • Work closely with analysts and business stakeholders to translate data requirements into technical solutions.
  • Ensure data logic aligns with business definitions and operational context.
  • Data Quality & Documentation
  • Implement data validation checks and tests to ensure accuracy and trustworthiness.
  • Maintain clear documentation of data models, transformation logic, and data lineage.
  • Use Git for version control and collaboration best practices.
  • Infrastructure Support
  • Support data infrastructure maintenance in cloud environments (BigQuery, Redshift, Snowflake).
  • Adapt to evolving infrastructure, tools, and processes in a fast-paced environment.

Requirements

  • Bachelor’s degree in Engineering, Computer Science, or a related technical field.
  • 1–2 years of experience in analytics engineering, data engineering, or equivalent data-focused roles.
  • Proficient in writing complex SQL queries.
  • Experience with dbt or similar data modeling tools.
  • Familiarity with Git (branching, commits, pull requests).
  • Exposure to cloud data warehouses (e.g., BigQuery, Redshift, Snowflake).
  • Understanding of data validation, quality testing, and documentation practices.
  • Familiarity with cloud platforms (e.g., GCP, AWS) is a plus.

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