Remote Data Engineer (Python, PySpark & Databricks)

Description:

• Design, build, and support scalable data pipelines using Python, Apache Spark, PySpark, and Databricks.
• Modernize and migrate legacy data processing workloads to secure, cloud-native platforms.
• Build and maintain batch data ingestion pipelines from structured and unstructured sources.
• Integrate data from REST APIs, SharePoint, document repositories, enterprise applications, and cloud platforms.
• Implement data quality, monitoring, observability, and operational controls.
• Optimize data workloads for performance, scalability, reliability, and cost efficiency.
• Develop document extraction, classification, metadata enrichment, and automation pipelines.
• Apply software engineering practices including Git, CI/CD, automated testing, and code reviews.
• Collaborate with architects, developers, tax subject matter experts, and platform teams.

Requirements:

• 3+ years of experience in data engineering.
• Strong Python development experience.
• Strong Apache Spark and PySpark experience.
• Hands-on experience with Databricks.
• Strong SQL and data modelling skills.
• Experience building, testing, deploying, and troubleshooting production ETL/ELT pipelines.
• Experience with Git-based source control and CI/CD pipelines.
• Experience consuming REST APIs for data ingestion, including authentication, pagination, and failure handling.
• Strong understanding of data quality, reliability, and data engineering best practices.

Benefits:

• A stable, long-term contract with opportunities for career growth.
• Private health insurance.
• A remote-friendly culture that promotes work-life balance.
• Continuous training, mentorship, and learning programs.
• Free access to AI training resources and state-of-the-art AI tools.
• Flexible Paid Time Off (PTO) policy and paid holiday days.
• Challenging, world-class software projects for clients in the US and LatAm.