Senior Data Engineer (Scala & PySpark)

Job Description

We are seeking an experienced and highly motivated Senior Data Engineer to join our team on a 5-month contract. The ideal candidate will have strong expertise in Scala and PySpark, with deep hands-on experience in distributed data processing and cloud environments.

You will be responsible for designing, developing, and optimizing large-scale data pipelines to support business intelligence, analytics, and operational needs.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Scala and PySpark

• Build and optimize distributed data processing solutions using Apache Spark and Hadoop

• Develop and manage structured and unstructured data solutions using SQL and NoSQL databases

• Implement efficient data modeling strategies for analytics and reporting

• Collaborate with cross-functional teams in Agile environments

• Contribute to CI/CD pipeline implementation and version control using Git

• Ensure performance optimization, scalability, and reliability of data workflows

• Work with cloud platforms (AWS, Azure, or GCP) to deploy and manage data solutions

• Troubleshoot complex data engineering challenges and provide innovative solutions

Requirements

• Minimum 8 years of hands-on experience in Data Engineering

• Strong proficiency in Scala and PySpark

• Solid understanding of distributed computing frameworks (e.g., Apache Spark, Hadoop)

• Experience working with SQL, NoSQL, and data modeling

• Familiarity with CI/CD pipelines, Git, and Agile methodologies

• Exposure to cloud platforms such as AWS, Azure, or GCP

• Excellent analytical, problem-solving, and communication skills

• Ability to work independently and in a fast-paced environment