Sharp Decisions · 10 hours ago
Software Engineer 2
Sharp Decisions is a company that specializes in information services, and they are seeking a skilled Software Engineer to join their team. The ideal candidate will work on a Scala-based data processing platform, focusing on designing, developing, and maintaining scalable services that manage large volumes of data.
B2BHuman ResourcesInformation TechnologyStaffing Agency
Responsibilities
Designing, developing, and maintaining robust, scalable services that process and manage large volumes of data
Qualification
Required
Proficiency in Scala, with experience using sbt for build management
Strong understanding of functional programming concepts
Experience with JSON serialization/deserialization (e.g., Circe)
Familiarity with cloud platforms (AWS and/or GCP), including authentication and authorization mechanisms (IAM, STS, AssumeRole, WebIdentity)
Experience integrating with AWS SDKs (S3, STS) in Scala
Experience with Google BigQuery and Dataflow for data processing and analytics
Experience with SQL and PostgreSQL for data storage and querying
Experience with asynchronous and concurrent programming (e.g., using FS2, cats-effect)
Familiarity with distributed messaging systems (e.g., Google Pub/Sub)
Ability to test and validate code effectively, with experience in unit, component, and integration testing
Ability to troubleshoot and resolve issues in distributed, cloud-based environments
Experience with version control systems (Git) and collaborative development workflows
Strong problem-solving and debugging abilities
Effective communication and collaboration in a team setting
Ability to write clear, maintainable, and well-documented code
Bachelors degree in Computer Science or related field, or equivalent experience
3+ years of professional software engineering experience, preferably in data engineering or backend systems
Preferred
Experience with Finagle or similar RPC frameworks
Familiarity with data pipeline orchestration and workflow management
Knowledge of containerization and deployment in Kubernetes environments