You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you.
Job responsibilities
- Executes standard software solution, design, development, and technical troubleshooting
- Writes secure and high-quality code using the syntax of at least one programming language with limited guidance
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards.
- Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
- Applies technical troubleshooting to breakdown solutions and solve technical problems of basic complexity
- Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development
- Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 2+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Proficient in coding ( Java or Python)
- Strong knowledge of relational databases/ Transact SQL and caching technologies (Oracle/Postgres/SQL Server/elastic etc)
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Overall knowledge of the Software Development Life Cycle
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
Preferred qualifications, capabilities, and skills
- Exposure to cloud technologies (e.g. AWS, Databricks, Snowflake)
- Business Intelligence Tools (Tableau/Business Objects/ThoughtSpot)
- Kafka Messaging
- Good to have -Knowledge of Databricks
- Scala, Apache Spark