Assist in developing and maintaining data pipelines in Azure Databricks using SQL and PySpark.
Support ingestion of data from various systems (e.g., SaaS applications, databases, reports) into the Data Lakehouse.
Build and maintain transformation logic to move data through Medallion Architecture layers.
Implement basic data validation and data quality checks to ensure reliable datasets.
Support orchestration and scheduling of pipelines using Azure Data Factory and Databricks Jobs.
Optimize queries and data models for performance in Databricks and downstream reporting tools.
Collaborate with analytics teams to prepare datasets used in Power BI dashboards and reporting.
Assist with documenting pipelines, data flows, and technical processes.
Monitor pipeline execution and troubleshoot data issues when they occur.

Bachelor’s or Master’s degree in computer science, Information Systems, Data Engineering, or a related field.
1+ year of experience working with data pipelines, analytics platforms, or data engineering tools (internships or academic projects acceptable).
Strong knowledge of SQL and experience querying large datasets.
Familiarity with Apache Spark or Databricks.
Basic experience with Python or PySpark for data transformation.
Understanding data warehousing and Lakehouse concepts (Medallion Architecture).
Experience or exposure to Azure Data Factory or similar orchestration tools.
Knowledge of Fivetran is a plus.
Familiarity with Azure cloud services is a plus.
Exposure to Power BI or other BI tools is beneficial.
Strong analytical thinking and problem-solving skills.
Ability to work collaboratively in a team environment and communicate effectively.

Junior Data Engineer

Key skills