Meaningful work,
meaningful life

Job Description:

We are seeking a highly skilled and experienced Snowflake Data Engineer to join our dynamic team. The ideal candidate will have between 6 to 11 years of experience in data engineering with a strong focus on building and optimizing data pipelines using Snowflake. You will play a critical role 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.

Key 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).