Data Engineer (Python, PySpark & Databricks)
New
D
DevsuTax technology
Workable workplace: remote; Workable locations: Colombia. ArgentinaContractMiddle
Salary not disclosed
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Job Details
- Experience
- 3+ years of experience in data engineering.
- Required Skills
- PythonSQLGitSparkCI/CDRESTful APIsData modelingDatabricksPySpark
Requirements
- Have 3+ years of experience in data engineering.
- Bring strong Python development experience.
- Have strong Apache Spark and PySpark experience.
- Have hands-on experience with Databricks.
- Have strong SQL and data modeling skills.
- Have experience building, testing, deploying, and troubleshooting production ETL/ELT pipelines.
- Have experience with Git-based source control and CI/CD pipelines.
- Have experience consuming REST APIs for data ingestion, including authentication, pagination, and failure handling.
- Have experience writing automated tests for data pipelines.
- Have a strong understanding of data quality, reliability, and data engineering best practices.
- Have strong problem-solving, communication, and collaboration skills.
Responsibilities
- 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 Git, CI/CD, automated testing, and code reviews to data engineering work.
- Build, deploy, troubleshoot, and maintain production ETL/ELT pipelines.
- Collaborate with architects, developers, tax subject matter experts, and platform teams.
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