Software Engineer II - AWS, Java/Scala/Python, Spark

uce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development.

• Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems.

• Proactively identify hidden problems and patterns in data and use these insights to drive improvements to coding hygiene and system architecture.

• Contribute to software engineering communities of practice and events that explore new and emerging technologies.

• Add to team culture of diversity, equity, inclusion, and respect.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 2+ years applied experience

• Gain hands-on experience in system design, application development, and testing.

• Become proficient in coding with Scala and Spark.

• Develop strong software engineering and object-oriented programming skills with expertise in Scala, Java, and frameworks like Apache Spark and Apache Airflow.

• Acquire experience in developing, debugging, and maintaining code in a large corporate environment using modern programming and database querying languages.

• Understand the overall Software Development Life Cycle and agile methodologies such as CI/CD, application resiliency, and security.

• Demonstrate knowledge of software applications and technical processes within disciplines like cloud, AI, machine learning, or mobile.

• Develop expertise in application, data, and infrastructure architecture disciplines, including microservices, APIs, and event-driven architecture.

• Achieve fluency in cloud-native architecture, design, and implementation, with a preference for AWS experience.

• Work in a big data environment, handling structured, semi-structured, and unstructured data.

• Gain experience with containers, Kubernetes, Docker, and real-time streaming technologies like Apache Kafka and Amazon Kinesis and use development tools such as Jenkins, SVN/Crucible/Jira, and Git/Stash.

Preferred qualifications, capabilities, and skills

• Design and develop data pipelines using Databricks and Snowflake to ingest, enrich, and validate data from multiple sources.
• Re-engineer and migrate on-premises data solutions to the cloud.
• Gain knowledge of traditional big data systems, such as Hadoop, Impala, Sqoop, Oozie, Cassandra, Hive, and HBase.