Role Summary

• Design, build, and maintain scalable data solutions that support reporting, self-service analytics, and advanced analytics.
• Work primarily on the organization's data platform, currently centered on Snowflake and IICS, to transform raw data into trusted, business-ready data assets.
• Partner closely with Data Analysts and source-system teams to translate business needs into data models, pipelines, and reusable data products.
• Use AI-assisted development practices across the full delivery lifecycle to improve design quality, development efficiency, testing, documentation, and technical communication.
• Apply modern data engineering practices while maintaining strong fundamentals in data modeling, ETL/ELT, orchestration, and data quality.

Responsibilities

Design, develop, and maintain data pipelines, transformations, and orchestration workflows that ingest, curate, and publish data for analytics use cases.

• Build and enhance data models based on business analysis and reporting requirements.
• Work with structured and semi-structured data from enterprise systems and files, including relational databases, JSON, and XML.
• Collaborate with Data Analysts, source-system developers, and business stakeholders to define requirements and deliver fit-for-purpose data solutions.
• Improve engineering productivity by using AI tools for code support, testing framework creation, documentation, diagramming, and solution exploration.
• Support data quality, performance optimization, maintainability, and operational reliability of data solutions.
• Enable business reporting, self-service analytics, and foundational data assets for advanced analytics and data science teams.
• Follow established organizational standards for governance, security, access control, and data handling.