Senior Scala Data Engineer

Pay Range: $55.00hr - $60.00hr

Job Overview:

Our client is seeking a highly skilled Scala Developer with extensive experience in building large-scale data processing and distributed applications. The successful candidate will possess strong expertise in Scala, Apache Spark, Hadoop, SQL, AWS, and Kafka, with experience developing high-performance, scalable data solutions in cloud environments.

Responsibilities:

• Design, develop, and maintain scalable applications and data processing pipelines using Scala and Apache Spark.
• Build and optimize big data solutions leveraging the Hadoop ecosystem.
• Develop and maintain real-time and batch data processing frameworks.
• Design and implement event-driven architectures using Kafka.
• Write complex SQL queries and optimize data models for performance and scalability.
• Deploy, monitor, and maintain applications on AWS cloud platforms.
• Collaborate with architects, data engineers, analysts, and business stakeholders to deliver data-driven solutions.
• Troubleshoot and resolve production issues while ensuring system reliability and performance.
• Participate in code reviews and contribute to best practices and technical standards.

Required Skills:

• Strong proficiency in Scala programming.
• Hands-on experience with Apache Spark and distributed data processing.
• Experience working with Hadoop ecosystem components.
• Strong knowledge of SQL and database optimization techniques.
• Experience with AWS cloud services and cloud-native architectures.
• Expertise in Apache Kafka for real-time streaming and messaging solutions.
• Strong understanding of data structures, algorithms, and distributed systems.
• Experience with Agile development methodologies and version control tools such as Git.

Preferred Qualifications:

• Experience with Spark Streaming, Structured Streaming, or similar technologies.
• Familiarity with containerization technologies such as Docker and Kubernetes.
• Knowledge of CI/CD pipelines and DevOps practices.
• Exposure to data lake and modern analytics architectures.