We are looking for a Senior Data Engineer to help build scalable, reliable, and reusable data solutions. In this role, you will focus on industrializing data pipelines, strengthening data contracts, and delivering high-quality analytical data to support rule compliance.

You will play a key role in evolving the data infrastructure, replacing interim solutions with production-ready pipelines, and enabling efficient onboarding of new countries and business segments.

Responsibilities

• Industrialize and optimize dbt pipelines, migrating data workflows from DuckDB to PostgreSQL and retiring interim PowerQuery solutions.
• Own the versioning of scope and constraints, ensuring consistency, traceability, and reliability across data processes.
• Define and maintain data contracts with Optim-core, ensuring the availability and quality of analytical data required for rule compliance.
• Build reusable and scalable onboarding processes to support the expansion into new countries and business segments.
• Develop and maintain data transformation workflows using Python, SQL, dbt, and PostgreSQL.
• Contribute to data architecture decisions, pipeline reliability, and engineering best practices.
• Collaborate with cross-functional teams to ensure data solutions meet business and technical requirements.

Requirements for this challenge

• Strong experience in software engineering, with a focus on data engineering or data-intensive applications.
• Proficiency in Python and SQL.
• Hands-on experience with dbt and building and maintaining data transformation pipelines.
• Experience working with DuckDB and PostgreSQL, including data migration and query optimization.
• Experience with Azure cloud environments.
• Understanding of data modeling, data quality, versioning, and data contracts.
• Ability to design reusable solutions that support scalability and maintainability.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills, with the ability to translate business needs into reliable technical solutions.

Nice to Have

• Experience migrating data workflows from interim tools to production-ready architectures.
• Familiarity with data governance, lineage, and data quality practices.
• Experience building reusable data processes for multiple countries, markets, or business segments.
• Experience integrating analytical data pipelines with downstream platforms or optimization engines.