Senior Data Engineer, Data Lake

Location: Remote, Brazil; candidates must be based in Brazil

Company

hirify.global is a global payments technology company facilitating transactions between consumers, merchants, financial institutions, and government entities.

What you will do

• Develop, test, and maintain data ingestion, transformation, and quality-check pipelines using PySpark, SparkSQL, and Databricks.
• Build and modify Airflow DAGs on MWAA for pipeline orchestration.
• Write and optimize SQL queries for data transformation and validation.
• Implement and monitor data quality checks using Great Expectations or an equivalent tool.
• Investigate pipeline failures and data quality issues, participate in code reviews, and maintain dataset and pipeline documentation.
• Participate in sprint planning, estimation, retrospectives, testing, CI/CD, and data governance activities.

Requirements

• Must be based in Brazil.
• English proficiency at B2 level or above.
• 3+ years of relevant experience with a Bachelor's or Associate’s Degree, or 5+ years of relevant experience.
• Experience with Python, data pipeline concepts, batch processing, and ETL/ELT patterns.
• Knowledge of Apache Spark, Databricks, intermediate-to-advanced SQL, Amazon S3 data lake design, AWS fundamentals, and data modeling.
• Experience with Git/GitHub workflows and code review.

Nice to have

• Experience with Delta Lake, Apache Airflow/MWAA, CDC patterns, data quality testing, Terraform, or BI integration with Superset.

Culture & Benefits

• Remote work is available, with possible scheduled visits to a hirify.global office.
• Work on a data platform supporting decision-making across the company and external clients.
• Contribute to global data infrastructure, secure self-service access, and high-quality reporting.
• Work within defined CI/CD, testing, governance, and code review standards.