Mid-Level Data Engineer

Job Mission: Execute and sustain data and machine learning (ML) pipelines, ensuring the quality, organization, and availability of datasets for analytical consumption by other company teams.

Key Responsibilities

• Build and maintain pipelines in Databricks using Delta Lake, Workflows, and Jobs.
• Develop routines for ingesting and transforming data from various sources.
• Prepare structured datasets for consumption in partner tools and BI platforms (Emblem, Power BI, Tableau, Radar).
• Support the creation and maintenance of the Data Feature Store to support modeling teams.
• Operate Machine Learning pipelines with MLflow support.
• Implement basic data quality and integrity checks.
• Monitor daily job execution and act proactively or reactively in case of failures.
• Ensure proper versioning, documentation, and organization of source code.

Technical Requirements and Education

• Education: Completed higher education in quantitative fields such as Statistics, Mathematics, Engineering, Computer Science, or related fields.
• Practical experience working with Databricks, Apache Spark, and SQL.
• Solid knowledge of Python programming focused on data manipulation.
• Experience in developing and maintaining data pipelines (ETL/ELT).
• Understanding of MLOps concepts and workflow orchestration tools (such as Airflow or similar).
• Basic knowledge of data governance and quality best practices.

Behavioral Profile

• Strong sense of organization and extreme attention to detail.
• Strong interpersonal communication skills to collaborate with multidisciplinary teams.
• Operational proactivity in identifying and quickly resolving failures.
• Constant desire to learn and stay updated with new data technologies.