Data Engineering Instructor

About the role

AmaliTech Rwanda is seeking a highly motivated and experienced Data Engineering Instructor to support both the Training Center and Service Center functions. The role focuses on delivering technical training, mentoring trainees, assessing progress, and contributing to industry‑ready data engineering talent.

Key responsibilities

• Deliver engaging technical training and mentorship in Data Engineering, covering Python, SQL, Apache Spark, Kafka, Airflow, and modern data architectures.
• Guide trainees in designing, building, and managing scalable ETL/ELT pipelines and cloud‑based data solutions using AWS and Microsoft Fabric technologies.
• Support learners in data visualization and business intelligence development using Power BI, including dashboard creation, DAX, Power Query, and data modeling.
• Assess, grade, and validate trainee projects, assignments, and technical assessments to ensure industry‑ready competency levels.
• Mentor trainees on best practices in data governance, CI/CD workflows, GitHub Actions, Delta Lake, and lakehouse architectures.
• Collaborate with internal technical teams to continuously improve curriculum content, training delivery, and learning outcomes.

Required profile

• Minimum of 2 years professional experience in Data Engineering or a related field.
• Strong proficiency in Python (Pandas, NumPy, PySpark) and SQL.
• Hands‑on experience with Apache Airflow, Apache Spark, and Apache Kafka.
• Practical knowledge of AWS data services (S3, Glue, Redshift, Kinesis, Lambda, DynamoDB, Step Functions, Athena).
• Experience with Microsoft Power BI (report/dashboard development, DAX, Power Query, data modeling).
• Familiarity with Microsoft Fabric (Lakehouse, Data Factory, Spark Notebooks, OneLake).
• Understanding of data engineering principles such as data modeling, schema design, ETL/ELT patterns, lakehouse architecture, Delta Lake, CDC, schema evolution, and data governance.
• Experience with CI/CD pipelines and GitHub Actions for data workflows.
• Previous teaching, mentoring, or facilitating technical learning programs is an advantage.

Required skills

• Python, Pandas, NumPy, PySpark
• SQL
• Apache Airflow, Apache Spark, Apache Kafka
• AWS S3, Glue, Redshift, Kinesis, Lambda, DynamoDB, Step Functions, Athena
• Microsoft Power BI, DAX, Power Query, data modeling
• Microsoft Fabric, Lakehouse, Data Factory, Spark Notebooks, OneLake
• Data modeling, schema design, ETL/ELT, Delta Lake, Change Data Capture, schema evolution, data governance
• CI/CD pipelines, GitHub Actions