Key Responsibilities

• Support the building and maintenance of data pipelines in a cloud environment.
• Assist in the integration of various data sources and the organization of datasets for analysis.
• Contribute to pipeline monitoring, tracking logs, metrics, and alerts to ensure data quality and reliability.
• Support the creation and maintenance of scripts, notebooks, and data processing jobs.
• Collaborate on code organization, versioning, and deployment automation alongside the data engineering team.
• Assist in data modeling and preparation for use in analytical tools.
• Provide support in optimizing reports and models in Power BI, following best practices for performance and governance.
• Support activities related to access management and integration between data environments.

Desired Technical Skills

• Basic or academic knowledge in data engineering or data analysis.
• Familiarity with cloud computing, preferably AWS (S3, Glue, Lambda, Redshift, or similar services).
• Familiarity or interest in working with Databricks or distributed data processing environments.
• Knowledge of SQL and data manipulation.
• Familiarity with code versioning (Git).
• Interest in learning about pipeline monitoring and data quality.
• Basic knowledge of Power BI or BI tools.

Differentiators

• Initial knowledge of Spark, Airflow, dbt, or data orchestration tools.
• Academic experience or personal projects involving ETL/ELT and data pipelines.
• Familiarity with software engineering best practices (CI/CD, automation, testing).
• Interest in learning about modern data architectures and Big Data.