Data Activation Engineer II

Job Overview

The IT Data Activation Engineer II is a mid-level developer responsible for designing, developing, and maintaining software applications. This role involves collaborating with cross-functional teams to analyze user requirements, implement solutions, and ensure high-quality code through testing and debugging. Developers are expected to participate in code reviews, coach and assist teammates, contribute to technical documentation, and stay up-to-date with industry trends, including the adoption and effective use of AI tools and technologies.

Duties & Responsibilities

• Development: Build, optimize, and maintain sophisticated data pipelines and models in Snowflake, applying best practices in star schema and dimensional modelling. This includes developing logical and physical data models, mapping source systems, and designing data flows to support analytics and reporting.
  • Design, implement, and manage ETL processes using DBT, SSIS and Azure Data Factory, ensuring efficient extraction, transformation, and loading of data from diverse sources. Architect ETL jobs to handle large volumes of data and maintain high performance and reliability
• Performance Monitoring: Monitor, troubleshoot, and refine data workflows, ensuring both data quality and alignment with modelling standards such as normalization, dimensional design, and efficient ETL practices
• Collaboration: Work closely with data analysts, business users, and IT teams to understand requirements and deliver solutions that meet organizational needs
• Learning: Stay up-to-date with updates, new features, and industry trends
• Support: Participate in on-call support rotations, routine maintenance activities, and other duties as determined by the team
• Coaching and Mentoring: Coach and help teammates by sharing knowledge, performing code reviews and providing feedback
• Other duties as assigned

Knowledge, Skills, & Abilities

• 3-5 years of practical experience with Snowflake, DBT, Azure cloud services, and demonstrated skill in designing and implementing star schema and other data modelling frameworks.
• Strong background in data modelling, including experience with dimensional modelling, entity-relationship models, normalization, and the creation of star and snowflake schemas. Proven ability to translate business requirements into effective data structures.
• 3-5 years hands-on experience designing, building, and maintaining ETL processes and workflows, preferably using DBT, Azure Data Factory, or similar tools.
• Advanced proficiency in SQL, and familiarity with data transformation techniques, source-to-target mapping, and ETL best practices.
• Strong SQL skills, including writing complex queries (joins, CTEs, window functions), query optimization, and troubleshooting performance issues.
• Python experience for scripting and automation (e.g., data validation, file processing, and API integration; familiarity with libraries such as pandas is a plus).
• Exposure to Snowflake Cortex (e.g., LLM functions and built-in AI capabilities) and interest in applying it to analytics and AI/ML enablement use cases.
• Hands-on experience with CI/CD tools and pipelines, including automated testing, deployment, and version control (e.g., Git, Azure DevOps).
• Ability and willingness to learn, adopt, and apply AI and machine learning technologies within data engineering workflows.
• Excellent problem-solving skills and attention to detail, particularly in structuring and optimizing data models and ETL pipelines.
• Strong communication and collaboration skills

Minimum Qualifications

• Two years of education beyond high school in college or technical school
• Three to up to five years relevant work experience

Preferred Qualifications

• Bachelor's degree, particularly in Information Systems, Computer Science, Engineering
• Certifications in Data Engineering, Snowflake, DBT preferred

Work Environment

• Office