We are looking for a highly skilled Snowflake Data Engineer with 6 to 11 years of experience to join our dynamic team. The ideal candidate will have extensive experience in data engineering with a strong emphasis on building and optimizing data pipelines using Snowflake. You will be pivotal in designing, developing, and maintaining our cloud-based data warehouse, ensuring efficient data processing and enabling advanced analytics across the organization.
Key Responsibilities
Data Warehouse Design & Development
- Design and implement scalable, efficient, and secure data pipelines to ingest, process, and store large volumes of structured and semi-structured data in Snowflake.
- Develop and maintain robust ETL/ELT processes using Snowflake features such as Streams, Tasks, and Snowpipe.
Performance Optimization
- Optimize Snowflake queries and data models for performance, ensuring low latency and high throughput.
- Implement clustering keys, materialized views, and other Snowflake best practices to enhance query performance.
Data Management & Security
- Manage data access controls and security measures in Snowflake using role-based access control (RBAC).
- Implement data governance policies, ensuring compliance with data privacy regulations.
Automation & Monitoring
- Automate routine data tasks using Snowflake’s automation tools and integrate them with CI/CD pipelines.
- Monitor data pipeline performance and troubleshoot issues to ensure data availability and reliability.
Collaboration & Documentation
- Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver data solutions.
- Document data models, pipeline workflows, and best practices to ensure knowledge sharing within the team.
Continuous Improvement
- Stay updated with the latest Snowflake features and industry trends, recommending and implementing improvements to the data platform.
- Participate in code reviews and mentor junior engineers, fostering a culture of continuous learning and improvement.
Experience & Qualifications
Experience
- 6 to 11 years of experience in data engineering, with at least 3+ years of hands-on experience working with Snowflake.
Technical Skills
- Strong expertise in Snowflake architecture, including virtual warehouses, micro-partitioning, and data sharing.
- Proficiency in SQL and experience with performance tuning in Snowflake.
- Experience with ETL/ELT processes and tools (e.g., dbt, Informatica, Matillion).
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and integration of Snowflake with cloud storage services.
- Knowledge of data modeling concepts and best practices.
- Experience with scripting languages (e.g., Python, Shell) for automation.
Soft Skills
- Excellent problem-solving and analytical skills.
- Strong communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
- Ability to work collaboratively in a fast-paced environment, managing multiple priorities.
Education
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field.
Preferred Certifications
- Snowflake SnowPro Certification or equivalent.
- Certifications in cloud platforms (e.g., AWS Certified Solutions Architect, Microsoft Certified, Azure Data Engineer).
Skills
- Primary Skill. Data Engineering
- Sub Skills. Data Engineering
- Additional Skills. ETL, Informatica, Snowflake, Azure Data Lake, Azure Data Factory
Apply Now
If you’re a motivated Snowflake Data Engineer looking to drive impactful data solutions in a leading technology company, we invite you to apply and join our innovative team at Infogain.