Data Engineering Intern

Key Responsibilities:

• Data Modelling & ETL:
  • Implement robust data models to support analytics and reporting.
  • Maintain scalable ETL processes from various sources into a data warehouse.
• Data Ingestion & Automation:
  • Implement data validation and quality checks to ensure accuracy.
  • Maintain automated data pipelines for efficient data processing.
  • Utilize orchestration tools for scheduling and monitoring workflows.
  • Collaborate with data analysts to support their analysis needs.
• Data Warehousing:
  • Optimize data warehousing solutions for business intelligence and analytics.
  • Implement data modeling techniques for optimal querying and analysis.
• Optimization & Performance Tuning:
  • Troubleshoot and improve existing reports and dashboards.
  • Optimize dashboard performance for large datasets and complex queries.

Experience & Qualifications:

• Experience:
  • 6+ months of industry experience in data engineering, focusing on data ingestion, warehousing, pipeline automation, and ETL development.
  • Programming experience in Python, Scala, or Java.
  • Proficiency with SQL and experience with Spark, Hadoop, Hive, or HDFS.
  • Working knowledge of databases and analytics solutions, including Amazon Redshift.
• Skills:
  • Experience with unit and integration testing.
  • Ability to gather requirements and communicate effectively with stakeholders across teams.
  • A proactive attitude and willingness to dive into complex challenges.
• Education:
  • Bachelor’s or Master’s degree in Computer Science, Mathematical Science, Machine Learning, or a related field.
• Languages:
  • Proficiency in English is required.
  • Knowledge of French is a plus.
• Technologies:
  • Python, Java, SQL, NoSQL, Amazon Redshift, Kafka, Apache Beam, Apache Airflow, Apache Spark.

Job Details:

• Work Hours: 8 hours per day
• Job Experience: No prior experience required beyond the 6-month industry experience.
• Education Level: Bachelor’s Degree