Staff Data Engineer

Posted 5 days agoViewed

💎 Seniority level: Staff, 7+ years

📍 Location: Latin America, EST, NOT STATED

🔍 Industry: AI economy, workforce development

⏳ Experience: 7+ years

🪄 Skills: PostgreSQLPythonSQLApache AirflowETLGCPGitKafkaMongoDBData engineeringCI/CDTerraformMicroservicesScala

7+ years in a Data Engineering role with experience in data warehouses and ETL/ELT.
Advanced SQL experience and skills in database design.
Familiarity with pipeline monitoring and cloud environments (e.g., GCP).
Experience with APIs, Airflow, dbt, Git, and creating microservices.
Knowledge of implementing CDC with technologies like Kafka.
Solid understanding of software development practices and agile methodologies.
Proficiency in object-oriented scripting languages such as Python or Scala.
Experience with CI/CD processes and source control tools like GitHub.

Act as the data lake subject matter expert to develop technical vision.
Design the architecture for a well-architected data lakehouse.
Collaborate with architects to design the ELT process from data ingestion to analytics.
Create standard frameworks for software development.
Mentor junior engineers and support development teams.
Monitor database performance and adhere to data engineering best practices.
Develop schema design for reports and analytics.
Engage in hands-on development across the technical stack.

Posted about 2 months ago

📍 Brazil

🧭 Full-Time

🔍 Corporate wellness

🔧 Requirements

Experience in creating robust and scalable data models from business requirements.
Collaborative skills for collecting, preparing, and analyzing complex business data.
Familiarity with machine learning and AI concepts, particularly in generative AI.
Knowledge of data pipeline tools and technologies like Airflow and Kafka.
Ability to collaborate with various teams to understand data needs and develop effective data pipelines.
Comfort with big data concepts to ingest, process, and provide data to business analysts and product teams.
Strong motivation to contribute to a data-driven culture.

💡 Responsibilities

Develop and maintain data models and structures for efficient querying and analysis.
Design, develop, and maintain data pipelines to transform and process large volumes of data from various sources.
Implement automated data quality checks to ensure data quality and consistency.

PythonSQLApache AirflowArtificial IntelligenceKafkaMachine LearningData modeling

Posted about 2 months ago