Junior Data Engineer

About the role

The Data Engineer is responsible for building and maintaining the data foundation that enables reliable reporting, analytics, and data-driven decision making. The role designs scalable data pipelines, develops and maintains the data warehouse, ensures data quality and integrity, and works closely with business and technical teams to turn requirements into actionable data solutions.

Key responsibilities

• Design, build, and optimize scalable ETL/ELT data pipelines to ensure high performance, reliability, and smooth data flow across systems.

• Architect and maintain robust data warehouse solutions. Apply advanced data modeling techniques, including Star/Snowflake schemas and strategic data partitioning.

• Implement comprehensive automated monitoring, alerting, and rigorous data quality checks data integrity and proactive error handling.

• Partner closely with cross-functional teams to translate complex business requirements into scalable, actionable data solutions.

Requirement

• Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline.

• Min. 2 years of hands-on experience in Data Engineering, Data Warehousing, or Data Analytics.

• Advanced proficiency in SQL and a deep understanding of relational database management systems (RDBMS), specifically in optimizing complex queries.

• Strong coding skills in Python, Go (Golang), or Scala for backend automation, scripting, and data manipulation.

• Hands-on expertise with workflow orchestration tools, particularly Apache Airflow or similar platforms.

• Solid grasp of modern ETL/ELT design patterns and fundamental data modeling principles.

• Experience with distributed data processing frameworks, specifically Apache Spark (PySpark/Spark SQL) (preferred).

• Familiarity with modern data transformation and analytics engineering tools like dbt (preferred).