Data Architectural Specialist

Há 2 dias

Guarulhos, São Paulo, Brasil beBeeDataEngineer Tempo inteiro US$3.000.000 - US$4.000.000
Data Engineering Role

We are seeking a talented Data Engineer to join our team. As a Data Engineer, you will be responsible for designing and building scalable, secure, and high-performance data architectures in cloud environments.

Our goal is to deliver a powerful digital ecosystem where the banked and unbanked connect. We aim to provide a one-stop shop for all financial needs, serving over 10 million users and processing more than $4 billion annually.

Key Responsibilities:
  • Design and build scalable, secure, and high-performance data architectures in cloud environments (AWS), applying architectural patterns like Lambda Architecture and domain-driven design.
  • Model data across conceptual, logical, and physical levels using dbt and ER modeling tools, ensuring data integrity, consistency, and alignment with architectural standards.
  • Develop optimized data structures to support regulatory reporting, analytics, and operational workloads with a strong focus on reliability and compliance.
  • Design, build, and maintain batch and real-time data pipelines using Airflow, Kafka, and Spark, integrating structured and unstructured data from multiple sources with low latency and high availability.
  • Optimize data ingestion, transformation, and delivery workflows to ensure timely and accurate regulatory reporting.
  • Build and manage scalable data platforms, including Data Lakes, Data Warehouses, and Lakehouses, utilizing technologies such as Snowflake, Redshift, and Delta Lake.
  • Continuously monitor and optimize platforms for performance, scalability, and cost-effectiveness.
  • Orchestrate complex workflows and automate data processes using Airflow, Databricks, or equivalent orchestration tools.
  • Implement best practices for pipeline modularization, versioning (Git), and active monitoring to ensure robustness and maintainability.
  • Implement layered security measures across data platforms, including encryption, RBAC, data masking, and auditing practices, leveraging tools like Ranger, IAM, and cloud-native solutions.
  • Ensure compliance with internal and external governance, security, and regulatory requirements across all data processes.
  • Document data flows, technical standards, architecture decisions, and operational procedures clearly and effectively.
  • Mentor and support other engineers in adopting engineering best practices, ensuring a high level of technical excellence and consistency across the team.

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