Top Scala Jobs in Richmond, VA

Lead a team to design and deliver cloud-based, distributed microservices and data platforms (Python/Scala/Spark/AWS). Mentor engineers, collaborate with product managers, evaluate and adopt new technologies, and help meet regulatory needs while occasionally coding and reviewing work.

Lead and mentor engineering teams to design and deliver cloud-based backend solutions using distributed microservices, modern languages and container orchestration on AWS. Collaborate with product, evaluate and write code, and drive technical transformation and regulatory-compliant systems.

Design, develop, and maintain scalable backend services and distributed systems using Scala, Java, and the Akka ecosystem; build RESTful APIs and cloud-native solutions on AWS; design data access with Slick/SQL; maintain CI/CD pipelines; participate in architecture, code reviews, troubleshooting, and performance improvements.

Design, develop, optimize, and deploy high-performance data processing applications using Scala and Apache Spark on Cloudera CDH. Build and tune ETL pipelines integrating HDFS, Hive, Impala, HBase, and Kafka. Ensure data integrity and security, troubleshoot performance, collaborate with data scientists and analysts, and implement version control and CI/CD.

Design, develop, optimize, and deploy large-scale data processing applications using Scala and Apache Spark within the Cloudera Hadoop ecosystem. Build ETL pipelines, ensure data integrity and performance, troubleshoot Spark/Cloudera issues, collaborate with data scientists and analysts, and implement version control and CI/CD for Spark applications.

Design, develop, optimize, test, and deploy large-scale Spark/Scala data processing and ETL pipelines within the Cloudera ecosystem. Collaborate with data scientists and analysts, ensure data integrity and security, troubleshoot performance issues, and implement version control and CI/CD for production data solutions.

Design, develop, optimize, and deploy high-performance Spark/Scala data processing applications and ETL pipelines within the Cloudera Hadoop ecosystem. Collaborate with data scientists and analysts, ensure data integrity and performance, troubleshoot Spark/Cloudera issues, and implement version control and CI/CD for Spark applications.