Scala Data Engineer

icon building Company : Cartney
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Job Description - Scala Data Engineer

Job Description: We are seeking a highly skilled Scala Data Engineer to join our dynamic team. The ideal candidate will be responsible for designing, developing, and maintaining our data infrastructure, ensuring it is robust, scalable, and efficient. You will work closely with data scientists, analysts, and other engineers to deliver high-quality data solutions that support our business goals.

Key Responsibilities:

  • Design, build, and maintain scalable data pipelines and ETL processes using Scala and other relevant technologies.
  • Collaborate with data scientists and analysts to understand data requirements and implement efficient solutions.
  • Optimize and tune data processes for performance and scalability.
  • Develop and maintain data models and schemas to support business intelligence and analytics.
  • Implement best practices for data management, including data quality, security, and governance.
  • Troubleshoot and resolve data-related issues, ensuring data integrity and consistency.
  • Stay current with emerging technologies and industry trends, recommending new tools and techniques as appropriate.

Requirements:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  • Proven experience as a Data Engineer with a strong focus on Scala.
  • Proficiency in big data technologies such as Apache Spark, Kafka, and Hadoop.
  • Experience with relational and NoSQL databases (e.g., MySQL, PostgreSQL, Cassandra, MongoDB).
  • Strong understanding of data warehousing concepts and ETL processes.
  • Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and related data services.
  • Excellent problem-solving skills and attention to detail.
  • Strong communication and collaboration skills, with the ability to work effectively in a team-oriented environment.

Preferred Qualifications:

  • Experience with data streaming technologies.
  • Knowledge of data visualization tools and techniques.
  • Understanding of machine learning concepts and frameworks.
  • Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).
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