Data Engineer (PySpark) - Technology - Remote

Overview

We are looking for a Semi-Senior PySpark Data Engineer who is eager to learn, take initiative, and contribute to the development of high-performance and scalable data pipelines.

In Short

• Design, develop, and optimize data pipelines using PySpark and Apache Spark.
• Integrate and process data from multiple sources (databases, APIs, files, streaming).
• Implement efficient data transformations for Big Data in distributed environments.
• Optimize code to improve performance, scalability, and efficiency in data processing.
• Collaborate with Data Science, BI, and DevOps teams.
• Monitor and debug data processes to ensure quality and reliability.
• Apply best practices in data engineering and maintain clear documentation.
• Stay up to date with the latest trends in Big Data and distributed computing.

Requirements

• 1-3 years of experience working with PySpark and Apache Spark in Big Data environments.
• Experience with SQL and relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, etc.).
• Knowledge of ETL processes and data processing in distributed environments.
• Familiarity with Apache Hadoop, Hive, or Delta Lake.
• Experience with cloud storage (AWS S3, Google Cloud Storage, Azure Blob).
• Proficiency in Git and version control.
• Strong problem-solving skills and a proactive attitude.
• A passion for learning and continuous improvement.

Benefits

• 100% Remote Work: Enjoy the freedom to work from the location that helps you thrive.
• Highly Competitive USD Pay: Earn an excellent, market-leading compensation in USD.
• Paid Time Off: Our paid time off policies ensure you have the chance to unwind.
• Work with Autonomy: Enjoy the freedom to manage your time as long as the work gets done.
• Work with Top American Companies: Grow your expertise on innovative projects.