• 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 
   

• 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
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
• Expert-level implementation skills with Java, AWS, Database technologies, Python, Scala, Spark. 
• Experience with the development and decomposition of complex SQL (RDMS Platforms)
• Experience with Data Warehousing concepts (including Star Schema) 
• Practical experience in delivering projects in Data and Analytics, Big Data, Data Warehousing, Business Intelligence. Familiar with relevant technological solutions and industry best practices
• Good understanding of data engineering challenges and proven experience with data platform engineering (batch and streaming, ingestion, storage, processing, management, integration, consumption)
• Familiar with multiple Data & Analytics technology stacks
• Aware of various Data & Analytics tools and techniques (e.g. Python, data mining, predictive analytics, machine learning, data modelling, etc.)
• Experience with one or more leading cloud providers (AWS/Azure/GCP)
• Experience across the whole Software Development Life Cycle
• Exposure to agile methodologies such as CI/CD, Application Resiliency, and Security 

Preferred qualifications, capabilities, and skills

• Ability to work fast and quickly ramp up on new technologies and strategies.
• Ability to work collaboratively in teams and develop meaningful relationships to achieve common goals. 
• Appreciation of Controls and Compliance processes for applications and data.  
• In depth understanding of data technologies and solutions is preferable. 
• Drive Process improvements and implement process changes as necessary.
• Knowledge of industry-wide Big Data technology trends and best practices