Senior Data Engineer joining a dynamic team to develop impactful data solutions for the finance sector. Focusing on data infrastructure and collaborating across engineering and product teams.
Responsibilities
Design, develop and support robust data infrastructure solutions focused 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 architecture, data governance and monitoring.
Requirements
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.
Practical knowledge of data governance, security and storage (e.g., S3, Redshift).
Strong analytical and 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 equivalent.
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 intelligent analysis and 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 growing company in the market.
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