Description:

Design, build, and maintain scalable data pipelines and architectures for analytical and operational workloads.
Develop and optimize ETL/ELT pipelines for efficient data extraction, transformation, and loading.
Collaborate with backend engineers to integrate data pipelines into cloud-native applications.
Manage and optimize cloud data warehouses, primarily BigQuery.
Implement data governance, security, and privacy best practices.
Collaborate with analytics teams to define data models and enable self-service reporting.
Develop and maintain data documentation, including data dictionaries and lineage tracking.
Monitor and optimize data pipelines for high availability and reliability.
Stay updated with emerging data engineering technologies and best practices.

Requirements:

Certified Snowpro.
5+ years of experience in data engineering with modern cloud-based data platforms.
Strong hands-on experience with Snowflake, including performance tuning and data modeling.
Advanced SQL skills for analytics engineering and data transformation.
Proficiency in Python for data processing and automation.
Experience with dbt or similar analytics engineering frameworks.
Familiarity with orchestration tools like Dagster or Apache Airflow.
Strong problem-solving skills and excellent English communication skills.

Modern tools and systems to support your work and professional growth.
An inclusive and safe work environment that celebrates diversity.
Generous training budgets and mentorship focused on AI expertise and critical human skills.
Ample vacation policy to promote work-life balance.
Flexible work arrangements, including remote and hybrid options.

Skills