Engenheiro de Dados SR

Your tasks

• Design, develop, and maintain scalable, efficient, and reliable data pipelines to support large-scale data processing.
• Implement data ingestion, transformation, and integration workflows using both batch and streaming architectures.
• Build and optimize data engineering solutions with Cloudera, Databricks, and Amazon Web Services (AWS).
• Develop data processing and transformation routines using Python, SQL, PySpark, and Apache Spark.
• Create, maintain, and improve ETL/ELT processes to ensure efficient and consistent data movement.
• Design and work with Data Lake, Lakehouse, and distributed processing architectures.
• Integrate data from multiple sources while ensuring data quality, consistency, integrity, and reliability.
• Monitor pipeline execution, processing jobs, and queries, identifying bottlenecks and implementing performance improvements.
• Apply best practices for data security, governance, cataloging, lineage, and observability.
• Contribute to the evolution of data architecture, platform modernization, and continuous process improvement.
• Collaborate with architecture, analytics, data science, and business teams to align data solutions with technical and business requirements.
• Support troubleshooting and maintain reliable, maintainable, and production-ready data workflows.

Requirements

• Proven experience working as a Senior Data Engineer, with strong expertise in data solution development, architecture, and optimization.
• Practical experience with Cloudera and Databricks, particularly in processing and transforming large volumes of data.
• Knowledge of AWS and its core services for data engineering and cloud-based data processing.
• Strong command of SQL and hands-on experience with Python and PySpark.
• Experience with Apache Spark and distributed data processing technologies.
• Solid understanding of ETL/ELT processes and relevant tools.
• Experience designing and working with Data Lake and Lakehouse architectures.
• Knowledge of data modeling and integrating information from multiple data sources.
• Experience with Git and code version control practices.
• Ability to monitor data pipelines, troubleshoot issues, and optimize processing performance.

Additional qualifications that would be an advantage

• Experience with AWS data services such as Amazon S3, AWS Glue, Amazon Redshift, AWS Lambda, and Amazon Athena.
• Familiarity with cloud-based data processing, workflow orchestration, and pipeline management services.
• Experience with Delta Lake and Hadoop ecosystem technologies, including Hive, HDFS, and Impala.
• Knowledge of Apache Kafka and real-time data processing architectures.
• Experience with Apache Airflow or similar orchestration tools.
• Familiarity with CI/CD practices, infrastructure as code, and automation.
• Experience implementing data governance, quality controls, security, and observability practices.
• Participation in data platform migration, modernization, and integration projects.

What we offer

• Opportunity to work on innovative technology and digital transformation initiatives.
• Collaborative environment that values innovation, continuous learning, and professional growth.
• Exposure to modern data engineering platforms and cloud technologies, including Cloudera, Databricks, AWS, and distributed processing frameworks.
• Opportunity to collaborate with multidisciplinary teams across architecture, analytics, data science, and business functions.
• An organizational culture focused on ethical practices, collaboration, diversity, and technical excellence.

How to apply

How Jobgether works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?

Other

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.