Junior Data Engineer (6-Month Engagement)

About this role

N-iX is looking for a Junior Data Engineer to join a data-focused team supporting the day-to-day operations and ongoing development of enterprise data solutions. This is a 6-month engagement with an opportunity to gain hands-on experience working with modern cloud data platforms, large-scale datasets, and production data pipelines. You will work closely with experienced Data Engineers, contributing to pipeline maintenance, troubleshooting, onboarding new data sources, and implementing well-defined enhancements across the data platform.

This role is ideal for engineers with 1-2 years of professional experience who want to deepen their expertise in data engineering and cloud technologies. About the Role As a Junior Data Engineer, you will help ensure the reliability and quality of data pipelines that support business-critical analytics and reporting. You'll participate in monitoring, troubleshooting, testing, and implementing data processing logic while following established engineering standards and delivery practices.

Under the guidance of senior team members, you will contribute to data ingestion processes, validation activities, technical documentation, and operational support, gaining exposure to modern technologies such as Azure, Databricks, PySpark, and Snowflake. Responsibilities Monitor and support scheduled and event-driven data pipelines, data processing jobs, reporting refreshes, and data quality checks. Execute standard data ingestion and refresh activities from multiple sources, including APIs, CSV files, syndicated datasets, and configuration inputs.

Implement well-defined Python, PySpark, and SQL changes, including new filters, transformations, mappings, validation rules, and minor pipeline enhancements. Perform schema validation, reconciliation checks, regression testing, and source-to-target data verification. Investigate pipeline failures, validation issues, missing data, rejected files, and reporting discrepancies. Troubleshoot first-line operational incidents using logs, job outputs, and monitoring tools.

Escalate complex technical or business-data issues with clear diagnostic information and supporting evidence. Maintain technical documentation, deployment notes, runbooks, configuration files, and operational records. Follow established engineering practices, including Git workflows, pull requests, code reviews, testing, and deployment procedures. Support onboarding of new data sources and contribute to continuous improvement initiatives.