The Junior Data Engineer will play a crucial role in building and maintaining the data foundations that support analytics,
reporting, and machine learning initiatives. This role is responsible for helping transform raw data from multiple sources into
reliable, high-quality, and business-ready datasets that enable better decision-making across the organization.
Working closely with data engineers, data analysts, and ML engineers, the Junior Data Engineer will support the
development of data pipelines, data quality processes, and monitoring practices in a cloud-based environment. This role is
ideal for someone eager to grow in data engineering, contribute to production-grade data solutions, and continuously learn
modern tools, processes, and best practices.
What you’ll be doing:
● Develop, maintain, and optimize ETL/ELT data pipelines using SQL and Python
● Collect and integrate data from multiple sources, including batch and near real-time systems
● Transform raw data into clean, validated, and business-ready datasets for analytics and machine learning use cases
● Implement data quality checks, validation, and QA processes to ensure data accuracy and reliability
● Write, test, and maintain SQL and Python code to support scalable and dependable data workflows
● Monitor data pipelines and assist in incident investigation, incident management, troubleshooting, and resolution
● Collaborate with data analysts, ML engineers, and other stakeholders to support evolving data requirements
● Contribute to documentation, knowledge sharing, and continuous improvement of data engineering practices
Technical Skills
- Basic experience with cloud platforms (GCP preferred)
- Working knowledge of SQL and Python
- Exposure to ETL/ELT concepts and data pipeline development
- Familiarity with version control (Git)
- Basic understanding of DevOps practices, such as:
CI/CD pipelines
Infrastructure as Code (e.g., Terraform)
● Awareness of agile software development methodologies
Operational Knowledge
● Familiarity with incident management concepts, such as monitoring,
alerting, and issue escalation in production systems
● Willingness to learn monitoring, alerting, and production support
practices
Soft Skills
● Clear and effective communication skills
● Ability to collaborate with cross-functional teams
● Adaptable and eager to learn new tools and technologies
● Good problem-solving mindset and attention to detail
