Senior Data Engineer developing solutions for high-impact data in the financial sector. Join an innovative and collaborative team with opportunities to grow.
Responsibilities
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 smooth integration between systems.
Diagnose and resolve performance, scalability and reliability incidents.
Apply and promote best practices in data architecture, governance and monitoring.
Requirements
Strong experience in 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.
Practical knowledge of data governance, security and storage (e.g., S3, Redshift).
Analytical problem-solving skills with a focus on operational efficiency.
Good communication skills and experience working collaboratively.
Preferred:
Certifications such as AWS Certified Solutions Architect or similar.
Familiarity with Trino for ad-hoc analysis.
Experience with monitoring tools such as Datadog or New Relic.
Knowledge of AI applied to data, especially RAG (Retrieval-Augmented Generation), for projects involving analysis and intelligent insight generation.
Benefits
Competitive compensation based on experience;
Opportunities for career growth and participation in strategic projects;
Dynamic and challenging work environment;
Opportunity to work at a rapidly expanding, market-leading company.
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