Job Summary
AI Solution Developer (Data + AI)
Key Responsibilities
- Design and develop data engineering pipelines and solutions on Snowflake, leveraging Python and SQL as the primary technology stack.
- Actively adopt and apply AI-assisted development tools (e.g., AltimateAI) in the data engineering lifecycle to improve development productivity, code quality, and turnaround time.
- Build and maintain scalable ETL/ELT pipelines, data models, and transformations, ensuring performance, reliability, and data quality.
- Extend beyond data engineering as needed to support other solution development work using Python and related supporting technologies.
- Work with the Azure tech stack where applicable, integrating Azure services into data and AI solutions as required by the project.
- Follow coding best practices, version control, and CI/CD processes to ensure maintainable and production-ready code.
- Stay current with emerging AI-assisted development tools and practices, proactively identifying opportunities to embed AI into the development workflow.
Skill Requirements
- 5+ years of experience in software/data engineering or related fields.
- Strong hands-on experience with Snowflake for data warehousing, modeling, and pipeline development.
- Strong programming experience in Python for data engineering and solution development.
- Strong experience with SQL coding, query optimization, and data transformation.
- Hands-on experience with Data Vault 2.0 modeling methodology for building scalable, auditable data warehouse architectures.
- Hands-on experience with DBT (Data Build Tool) for data transformation, testing, and pipeline orchestration.
- Demonstrated ability and willingness to adopt AI tools (e.g., AltimateAI) in the development process to improve productivity.
- Demonstrated ability to quickly build AI solution through streamlit or any similar framework.
- Experience building and maintaining data pipelines, ETL/ELT processes, and data models in a cloud data warehouse environment.
- Solid understanding of coding best practices, version control (e.g., GitHub), and CI/CD concepts.
- Flexible and adaptable to work on other Python-based solution development beyond core data engineering tasks.
- Strong problem-solving skills with good communication and stakeholder management abilities.