Jr. Analytics Engineer
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Summary
Build and maintain data pipelines and transformations, design data models, and ensure data quality using SQL, Python, and PySpark on cloud data platforms.
Responsibilities
- Build and maintain data pipelines and transformations for analytics/reporting
- Create clean, structured datasets that are easy for BI tools and analysts to use
- Design data models (fact & dimension tables) for scalable analytics
- Write and manage data processes using SQL, Python, and PySpark
- Ensure data quality through validation and checks
- Optimize data performance (faster queries, efficient tables)
- Define metrics, data logic, and business rules clearly
- Work with stakeholders to turn business needs into data solutions
- Support dashboards, reporting, and self-service analytics
- Follow best practices (testing, documentation, deployment)
Qualifications
- Knowledge in SQL and Python
- Experience with large-scale data tools (e.g., PySpark/Spark)
- Good understanding of data modeling (fact/dimension tables)
- Familiar with ETL/ELT pipelines and data workflows
- Experience with cloud data platforms (Fabric, AWS, or GCP)
- Understand how data is used in dashboards and analytics tools
- Able to translate business needs into data models