Data Engineer, Mid-Level

• Build and enhance scalable data pipelines.
• Develop data ingestion, transformation, and delivery processes.
• Work with Spark and Databricks using a medallion architecture.
• Orchestrate data workflows and pipelines.
• Ensure data quality, governance, and observability.
• Optimize processing performance and costs.
• Contribute to engineering best practices, version control, and documentation.
• Support BI, Analytics, and AI teams and projects.

• Bachelor’s degree in Information Technology, Engineering, or a related field.
• Experience in data engineering and ETL/ELT pipeline development.
• Proficiency in Python and advanced SQL.
• Experience with Spark and Databricks.
• Knowledge of Lakehouse/Data Lake architecture.
• Experience with orchestration tools such as Apache Airflow.
• Knowledge of analytical data modeling (Star Schema, Snowflake, OBT, among others).
• Experience with data ingestion and integration tools (e.g., Azure Data Factory, Airbyte, etc.).
• Git and software development best practices.

• Professional development opportunities
• Dynamic work environment
• Encouragement of initiative, innovation, and learning from mistakes
• Recognition of efforts and celebration of achievements
• Diverse and inclusive work environment
• Affirmative-action positions for people with disabilities