Design, develop and support robust data infrastructure solutions with a focus on scalability, security and efficiency.
Lead the implementation and maintenance of ecosystems such as Trino, AWS Glue, Redshift, Airflow, Kafka and Spark on Kubernetes (K8s).
Collaborate with engineering, data science and product teams to ensure seamless integration between systems.
Diagnose and resolve performance, scalability and reliability incidents.
Apply and promote best practices in architecture, data governance and monitoring.

Strong experience with data infrastructure ecosystems: Trino, AWS Glue, Terraform, CI/CD, Apache Airflow, Kafka and Spark on Kubernetes.
Proven experience with cloud computing (AWS).
Advanced proficiency in Python (including PySpark) and object-oriented programming.
Demonstrated experience with distributed systems, data warehouses and large-scale ETL/ELT pipelines.
Hands-on knowledge of data governance, security and storage (e.g., S3, Redshift).
Analytical problem-solving skills with a focus on operational efficiency.
Strong communication skills and experience working collaboratively.

Preferred qualifications:

Certifications such as AWS Certified Solutions Architect or similar.
Familiarity with Trino for ad-hoc analytics.
Experience with monitoring tools such as Datadog or New Relic.
Knowledge of AI applied to data, especially RAG (Retrieval-Augmented Generation), for analytics and intelligent insight generation projects.

Senior Data Engineer

Key skills