Data & AI Engineer
Role details
Job location
Tech stack
Job description
- Design and implement end-to-end data pipelines that transform raw data into valuable insights, ensuring scalability and reliability in cloud environments.
- Develop and optimize data models with a focus on query performance and efficient workloads.
- Collaborate with cross-functional teams to translate business requirements into technical solutions, defining clear interface contracts between data products and applications.
- Enforce data quality, standardization, observability, and governance across systems, aligning with industry compliance standards and data privacy requirements.
- Automate data ingestion processes and monitoring systems to track operational KPIs, troubleshoot issues, and maintain pipeline health.
- Build and maintain ETL processes and machine learning workflows, providing clean AI ready data for our applications.
- Actively contribute to transversal data engineering best practices, including design patterns, CI/CD integrations, containerized deployments, also participate in peer review of code and technical documentation.
Requirements
Strong track record in designing and implementing data pipelines and data warehouse solutions in cloud environments.
Hands-on experience with data modeling, ETL/ELT processes, and pipeline orchestration in production settings.
Experience working in cross-functional teams, translating business needs into technical solutions.
Technical Skills:
Strong proficiency in SQL and data warehousing platforms (Snowflake preferred).
Hands-on experience with ETL tools (IICS or equivalent), data transformation tools (dbt preferred) and Python for data processing.
Strong experience with cloud platforms (AWS preferred) including orchestration frameworks (Airflow preferred).
Strong experience with Generative AI technologies and best practices (e.g. Vector Databases).
Good knowledge of CI/CD practices (GitHub Actions preferred), version control (Git), and infrastructure as code principles (Terraform preferred).
Experience in designing and implementing engineering patterns and technical standards.
Soft Skills:
Collaborative mindset with strong problem-solving abilities.
Self-motivated and able to take initiative in a fast-paced environment.
Effective communication skills to work with both technical and business stakeholders.
Education: Master's degree in Computer Science, Engineering, or a related field.
Languages: English is mandatory