Junior Data Engineer (6-Month Engagement) (#5893)

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.

• 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.

• 1-2 years of professional experience in Data Engineering, ETL/ELT development, Analytics Engineering, or Data Support roles.
• Good working knowledge of Python and SQL.
• Understanding of data pipelines, data transformations, batch processing, and ETL/ELT concepts.
• Familiarity with relational databases and data warehouse concepts.
• Experience working with API integrations and file-based data processing (CSV, Parquet, etc.).
• Hands-on experience with Git, version control workflows, pull requests, and code reviews.
• Understanding of data quality principles, including validation, reconciliation, schema checks, and error handling.
• Ability to analyze logs, troubleshoot issues, and communicate findings clearly.
• Strong analytical and problem-solving skills.
• Intermediate or higher English level.
• Experience with Azure Data Factory, Azure Databricks, PySpark, Snowflake, Delta Lake, Azure Data Lake Storage, or similar cloud data technologies.
• Exposure to modern data platform architectures, including Medallion (Bronze-Silver-Gold) data processing patterns.
• Familiarity with Power BI or other BI/reporting platforms.
• Knowledge of cloud environments and DevOps practices.
• Experience with data validation frameworks such as Pandera.
• Understanding of CI/CD pipelines and deployment processes.