Especialista de Engenharia de Dados II – Tech Lead

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Define and enhance the corporate architecture of Lakehouse, ensuring scalability, security, governance, and high performance.

• Engage in the establishment of standards, models, and best practices for Data Mesh, supporting domains in the construction of data products.

• Promote solid technical choices involving Databricks, Delta Lake, Spark, AWS, and modern data ecosystems.

• Establish architectural references for batch and streaming pipelines, including best practices for orchestration, versioning, monitoring, resilience, and optimization.

• Guide and mentor data engineers, influencing critical decisions and elevating the technical standards of the organization.

• Conduct technical reviews (architecture, code, standards, pipeline design).

• Serve as an internal consultant for business units, ensuring a thorough understanding of solutions.

• Design and develop robust and scalable pipelines in Python, Scala, SQL, or Java within the Databricks and/or AWS ecosystem.

• Build real-time ingestion solutions using Spark Structured Streaming, Delta Live Tables, Kafka/Kinesis, or similar tools.

• Ensure observability (monitoring, alerts, and metrics) and data quality throughout the entire pipeline.

• Interact with business units, partners, suppliers, and third parties.

• Facilitate discovery, design, and support processes in the implementation of data products.

• Translate business needs into scalable and sustainable technical solutions.

• Disseminate knowledge about Lakehouse, Data Mesh, and batch and streaming pipelines.

• Conduct workshops, reference guides, mentoring, and internal technical communities.

• Foster a modern data culture and best engineering practices throughout the organization.

⛳️ Requirements

• Advanced English for communication with teams from other countries within the group.

• Solid experience as a data engineer, architect, or tech lead in large-scale environments.

• Proficiency in Databricks (Spark, Delta Lake, workflows, cluster management).

• Practical experience with AWS (S3, IAM, Glue, Lambda, Lake Formation, among others).

• Strong knowledge of Python, SQL, Scala, and/or Java.

• Experience in building batch and streaming pipelines.

• Familiarity with Data Mesh models, Lakehouse, distributed governance, and data products.

• Technical leadership ability, influence, and clear communication skills.

• Experience with CI/CD, versioning, data architecture, and best engineering practices.

🏝️ Benefits

• Wellness program.

• Opportunities for professional development.

• Inclusive work culture.