Senior Data Engineer

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

📋 Description

• Design, develop, test, and maintain scalable data pipelines and ETL/ELT processes.

• Construct and enhance data transformation workflows utilizing Python, SQL, and dbt.

• Create and uphold data ingestion, synchronization, and integration pipelines with Airbyte.

• Design and refine data models, transformations, and queries within Snowflake.

• Extract, transform, and integrate data from relational databases, particularly MySQL.

• Implement data quality checks, validation processes, error handling, and monitoring for pipelines.

• Diagnose pipeline failures, conduct root cause analysis, and apply sustainable solutions.

• Develop clean, reusable, maintainable, and well-documented code along with SQL transformations.

• Collaborate with engineers, analysts, developers, and stakeholders to deliver dependable data solutions.

• Engage in technical estimation and development planning activities.

• Enhance pipeline performance, scalability, reliability, and cost-effectiveness.

⛳️ Requirements

• Extensive professional experience in data engineering at a senior level.

• Strong skills in Python for data processing, automation, and pipeline development.

• Advanced SQL expertise, including complex queries, data transformations, and performance optimization.

• Documented experience in designing, developing, and maintaining ETL/ELT pipelines.

• Practical experience with dbt for data transformation, modeling, testing, and documentation.

• Hands-on experience with Airbyte for data ingestion, synchronization, and integration tasks.

• Strong background with Snowflake, encompassing data warehousing, modeling, and query optimization.

• Familiarity with relational databases, especially MySQL.

• Solid understanding of data warehousing, dimensional modeling, and data pipeline architecture.

• Proven experience in implementing data quality validation, error handling, and pipeline monitoring.

• Familiarity with Git, version control, and collaborative development workflows.

• Experience with CI/CD pipelines and contemporary data engineering practices.

• Practical experience utilizing AI-assisted software development tools.

• Strong debugging, troubleshooting, and analytical problem-solving capabilities.

• Ability to work independently, collaborate effectively, and take ownership of deliverables.

• Nice to have: Experience with cloud platforms (AWS, Azure, or Google Cloud), Docker, and modern data lake architectures.

• Nice to have: Familiarity with Agile methodologies, data governance, security, and access control best practices.

🏝️ Benefits

• Continuous learning environment.

• Cutting-edge benefits, tools, and resources.

• English scholarships for an external institute.

• English classes with company teachers.

• State-of-the-art tools and resources.

• Certifications for professional growth.

• Recreation and leisure activities.

• Compliance with the regulations and labor rights of your region.

• Great Place To Work certification.