An established industry player is seeking a skilled Data Engineer to join their innovative team. In this role, you will leverage your expertise in Snowflake and cloud technologies to create and implement enterprise-level applications. You'll be responsible for designing features for identity and access management, optimizing client queries, and solving performance issues. This position offers the opportunity to work with cutting-edge data warehousing concepts and cloud migration strategies, making a significant impact on the organization's data infrastructure. If you're passionate about data and cloud solutions, this role is perfect for you.
Qualifications
10+ years of experience in data engineering and cloud technologies.
Strong knowledge of SQL and data warehousing concepts.
Responsibilities
Create and implement enterprise-level applications using Snowflake.
Migrate solutions from on-premises to cloud-based platforms.
Skills
Snowflake
DBT
SQL
Python
Datastage or Informatica
Unix
Tools
AWS
Azure
Job description
Experience
Experience: 10+ years
Mandatory skills
Snowflake
DBT
SQL
Python
Datastage or Informatica
Unix
Detailed Job Description
Knowledge of SQL language and cloud-based technologies
Data warehousing concepts, data modeling, metadata management
Data lakes, multi-dimensional models, data dictionaries
Migration to AWS or Azure Snowflake platform
Performance tuning and setting up resource monitors.
Snowflake modeling – roles, databases, schemas
SQL performance measuring, query tuning, and database tuning
ETL tools with cloud-driven skills
Roles and Responsibilities
Create, test, and implement enterprise-level apps with Snowflake.
Design and implement features for identity and access management.
Create authorization frameworks for better access control.
Implement Client query optimization, major security competencies with encryption.
Solve performance issues and scalability issues in the system.
Transaction management with distributed data processing algorithms.
Possess ownership right from start to finish.
Build, monitor, and optimize ETL and ELT processes with data models.
Migrate solutions from on-premises setup to cloud-based platforms.