Mastech Digital
Scala Developer
Location:
Whippany, New Jersey, Hybrid: 3 days onsite
Duration:
Long-Term Contract
Description:
We’re looking for an experienced Scala Developer who can design and build high-performance data processing systems within a large-scale distributed environment. You’ll work closely with Data Engineers, Architects, and Product teams to develop reliable data pipelines and contribute to our enterprise Big Data platform.
Key Responsibilities
Design, develop, and maintain scalable data pipelines using Scala and Spark
Implement efficient ETL/ELT solutions for large datasets across Hadoop, Databricks, or EMR environments
Optimize data processing performance and ensure code quality through testing and best practices
Collaborate with cross-functional teams on data architecture, schema design, and performance tuning
Develop reusable components and frameworks to support analytics and machine learning workloads
Work with Kafka, Hive, HDFS, and Delta Lake for data ingestion and storage
Contribute to CI/CD and automation using Git, Jenkins, or Azure DevOps
Required Skills & Experience
9+ years of hands‑on experience in Scala development (functional and object‑oriented)
5+ years of experience with Apache Spark (core, SQL, structured streaming)
Solid understanding of distributed data processing and storage systems (HDFS, Hive, Delta Lake)
Experience with Kafka or other event streaming technologies
Strong SQL and performance optimization skills
Familiarity with cloud platforms such as Azure, AWS, or GCP (preferably with Databricks)
Experience working in Agile/Scrum teams
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Whippany, New Jersey, Hybrid: 3 days onsite
Duration:
Long-Term Contract
Description:
We’re looking for an experienced Scala Developer who can design and build high-performance data processing systems within a large-scale distributed environment. You’ll work closely with Data Engineers, Architects, and Product teams to develop reliable data pipelines and contribute to our enterprise Big Data platform.
Key Responsibilities
Design, develop, and maintain scalable data pipelines using Scala and Spark
Implement efficient ETL/ELT solutions for large datasets across Hadoop, Databricks, or EMR environments
Optimize data processing performance and ensure code quality through testing and best practices
Collaborate with cross-functional teams on data architecture, schema design, and performance tuning
Develop reusable components and frameworks to support analytics and machine learning workloads
Work with Kafka, Hive, HDFS, and Delta Lake for data ingestion and storage
Contribute to CI/CD and automation using Git, Jenkins, or Azure DevOps
Required Skills & Experience
9+ years of hands‑on experience in Scala development (functional and object‑oriented)
5+ years of experience with Apache Spark (core, SQL, structured streaming)
Solid understanding of distributed data processing and storage systems (HDFS, Hive, Delta Lake)
Experience with Kafka or other event streaming technologies
Strong SQL and performance optimization skills
Familiarity with cloud platforms such as Azure, AWS, or GCP (preferably with Databricks)
Experience working in Agile/Scrum teams
#J-18808-Ljbffr