Water resource engineer - in - training supporting flood, river, stormwater, and watercourse projects at Onterris. Assisting modelling, design, field investigations, and regulatory work.
About the role
- Senior Snowflake Engineer responsible for designing, building, and optimizing cloud data platform. Collaborating with stakeholders to deliver secure data solutions powering analytics and decision-making.
Responsibilities
- Design, develop, and maintain scalable data pipelines and ELT/ETL workflows on Snowflake, integrating data from diverse internal and external sources.
- Architect and optimize Snowflake data models, schemas, and warehouses for performance, reliability, and cost efficiency.
- Implement and enforce data governance, security, role-based access controls, and data quality standards across the platform.
- Monitor and tune warehouse performance, query execution, and resource consumption to control costs and meet SLAs.
- Build and maintain CI/CD pipelines for data infrastructure using tools such as dbt, Git, and orchestration frameworks (e.g., Airflow).
- Leverage advanced Snowflake features — Snowpipe, Streams, Tasks, Time Travel, Dynamic Tables, and Snowpark — to deliver near-real-time and automated data solutions.
- Collaborate with analysts, data scientists, and business stakeholders to translate requirements into robust data solutions.
- Mentor junior engineers, conduct code reviews, and establish best practices for data engineering across the team.
Requirements
- 5+ years of data engineering experience, with 3+ years of hands-on Snowflake development in a production environment.
- Expert-level SQL skills, including complex query design, optimization, and performance tuning.
- Strong experience designing dimensional and/or data vault data models and building ELT pipelines.
- Proficiency with dbt for data transformation and modeling.
- Hands-on experience with at least one cloud platform (AWS, Azure, or GCP) and its data services.
- Programming proficiency in Python for data processing, automation, and scripting.
- Proficiency using GenAI and AI-assisted development tools (e.g., Claude Code, ChatGPT/OpenAI, GitHub Copilot, Cursor) to accelerate coding, debugging, and documentation.
- Experience with workflow orchestration tools such as Airflow, Dagster, or Prefect.
- Solid understanding of data warehousing concepts, data governance, and security best practices.
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
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