Senior Python Data Engineer

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

📋 Description

• Design, develop, and maintain scalable applications and services using Python.

• Create reusable, maintainable, and thoroughly documented code components.

• Develop backend services and APIs utilizing Django and/or Flask frameworks.

• Engage in architecture reviews and participate in technical design discussions.

• Troubleshoot and optimize existing production systems.

• Create and enhance large-scale data processing pipelines leveraging PySpark.

• Process, transform, and analyze extensive structured and unstructured datasets.

• Construct scalable ETL and data ingestion frameworks.

• Improve distributed data processing workloads for enhanced performance and reliability.

• Implement data science algorithms and predictive models in production settings.

• Collaborate with data scientists to operationalize machine learning solutions.

• Develop and refine ML pipelines using scikit-learn and other related libraries.

• Assist in model deployment, validation, and monitoring processes.

• Conduct complex data wrangling, cleansing, and transformation tasks.

• Build data pipelines utilizing Pandas, NumPy, PyArrow, and PySpark.

• Create solutions for managing large-scale datasets and analytical workloads.

• Design and develop RESTful APIs that support high-volume data operations.

• Construct secure, scalable services capable of handling substantial throughput.

• Design and optimize data access patterns across both relational and NoSQL databases.

• Utilize efficient SQL queries and handle database integrations.

⛳️ Requirements

• Over 8 years of professional experience in Python development.

• Demonstrated experience in developing enterprise-scale applications and data processing solutions.

• Proficient in working with large-scale datasets and big data platforms.

• Experience collaborating with global and distributed teams.

• Expert-level proficiency in Python programming.

• Solid understanding of object-oriented programming principles.

• Proven track record in developing scalable and maintainable applications.

• Extensive experience with Django and Flask frameworks.

• Background in building production-grade REST APIs.

• Strong hands-on experience with PySpark.

• Expertise in handling high-volume datasets.

• Experience in implementing and operationalizing data science algorithms.

• Practical experience with scikit-learn.

• Familiarity with Pandas, NumPy, PyArrow, and other Python data processing libraries.

• Extensive experience with relational databases such as PostgreSQL, SQL Server, Oracle, and MySQL.

• Strong SQL development capabilities.

• Experience with Cassandra, HBase, and other distributed NoSQL platforms.

• Strong commitment to automated testing, code reviews, CI/CD, source control, and software engineering best practices.

🏝️ Benefits

• Equipment: Provided by the client.

• Client Holidays (USA – Mandatory)