Design, build and maintain scalable, high-performance data pipelines that handle large volumes of data from multiple sources.
Manage and monitor data infrastructure, identifying and resolving performance bottlenecks and ensuring availability.
Ensure data security, quality and compliance, aligning with governance policies and applicable regulations.
Define, promote and ensure adoption of standards, best practices and data engineering frameworks across teams.
Document architectures, pipeline strategies, data flows and technical processes.
Support the technical development of the team’s data engineers by providing guidance and ongoing support.
Troubleshoot and resolve complex issues, providing specialized technical support.
Communicate with clients and stakeholders, translating technical concepts clearly, concisely and accessibly.

Degree in Computer Science, Engineering or a related field.
Minimum of 4 years of experience as a Data Engineer or in a similar role.
Proficiency in SQL and Python.
Experience with relational databases and data modeling.
Experience with cloud services and resources (Azure, AWS or GCP).
Familiarity with tools and platforms such as Spark/PySpark, Talend, Apache Hop, Pentaho, Airbyte, Data Factory, Airflow, dbt Core/Cloud, Databricks, Glue, Fabric, Snowflake, Synapse, Redshift, BigQuery, Athena, Dremio.
Solid understanding of Data Warehouse, Data Lake, Lakehouse and Medallion Architecture fundamentals.
Experience communicating directly with clients and stakeholders.

Mid-Level Data Engineer

Key skills