Junior Data Engineer
About The Position
The Junior Data Engineer helps build, maintain, and strengthen the data platform that supports dashboards, planning, and daily reporting across Kreate. The role works with data from the ERP, HR systems, and retail feeds as it moves through a Microsoft Fabric lake house using Bronze, Silver, and Gold layers. Working alongside a Senior Data Engineer, the Junior Data Engineer will gain hands-on experience building data pipelines, improving data quality, and supporting reliable, production-ready data infrastructure. The role also takes ownership of daily pipeline monitoring and troubleshooting while developing the skills needed to build data solutions end to end.
Requirements
- 1–3 years of experience in data engineering, analytics engineering, software development, or a related field. Internships and substantial academic or personal projects may count toward experience.
- Solid SQL skills, including joins and window functions, with an understanding of how joins can unintentionally multiply or "fan out" rows.
- Working knowledge of Python, including pandas or PySpark.
- Everyday experience using Git and version control.
- Strong attention to detail and patience for investigating existing pipelines and determining why a data result or metric has changed.
- A strong commitment to data accuracy and quality, with the judgment to flag discrepancies rather than deliver numbers that simply appear reasonable.
- Strong problem-solving skills and an interest in learning data engineering practices, tools, and technologies.
Nice To Haves
- Experience with Microsoft Fabric, Azure Data Factory, Databricks, or Synapse.
- Familiarity with Delta Lake and Parquet.
- Basic knowledge of Azure services such as App Service, Container Apps, Key Vault, and Entra ID.
- Experience working with ERP or manufacturing data, including Oracle, IQMS/DELMIAworks, SAP, or Epicor.
- Experience with Power BI.
Responsibilities
- Build and maintain data ingestion pipelines and notebooks in Microsoft Fabric, including Data Factory pipelines, Python/Spark notebooks, and Delta tables.
- Monitor the daily operation of scheduled pipelines and container jobs, triage failures, and ensure partially failed jobs are accurately reported as failures rather than successful runs.
- Develop and maintain data quality checks for data freshness, row counts, duplicate records, and reconciliation back to source systems, including appropriate alerts for issues.
- Migrate ad-hoc and desktop-scheduled scripts to managed, version-controlled, and monitored infrastructure.
- Model new source tables into conformed Silver dimensions and Gold facts, with clearly documented data grain and business definitions.
- Maintain runbooks and the data catalogue to ensure data pipelines, processes, and systems are well documented and maintainable.
- Work alongside senior engineering team members to troubleshoot pipeline issues, understand root causes, and build reliable solutions.
- Collaborate with data, analytics, and business teams to ensure data is accurate, accessible, and fit for downstream reporting and analysis.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
No Education Listed
