Вакансия Data Architect

• Snowflake Data Cloud

Описание вакансии

Responsibilities

• Data Architecture Design: Lead the design and documentation of sophisticated data architecture solutions, including data models, data integration patterns, and data storage mechanisms.
• Data Governance: Collaborate with data stewards and enforce robust data governance policies and practices to ensure data integrity, security, and compliance.
• Data Strategy Execution: Collaborate with engineering managers and the data engineering team to implement data solutions that aligned with the organization's strategic goals.
• Data Integration: Work alongside solution architects and data engineers to ensure seamless integration of data pipelines and data products with the overall data architecture.
• Data Quality Assurance: Oversee data quality measures and monitoring processes to ensure the accuracy and reliability of data. Contribute in the data quality process with improving models and pipelines
• Data Warehouse Migration: guide the migration from our current in-house data warehouse to Snowflake, focusing on strategic planning, risk management, and execution.
• Cloud Optimization: Optimize data storage and retrieval processes to fully leverage Snowflake’s capabilities, focusing on performance, scalability, and cost efficiency.

Requirements

• Data Expertise: Extensive experience in data engineering, data modeling, database design, data warehousing, and data governance practices.
• Cloud Data Warehousing: Specific experience with cloud data warehousing technologies, especially Snowflake, including its architecture and scaling capabilities. Proven knowledge of Snowflake will be considered a significant plus.
• Migration Expertise: Solid background in data warehouse migration projects, including familiarity with migration tools, strategies, and challenges associated with transitioning from an on-premise to a cloud-based environment.
• Data Strategy: Ability to develop and execute a data architecture strategy that supports data-driven initiatives and future growth.
• Data Standards: Deep knowledge of industry best practices and standards in data management, data security, and data quality.
• Collaboration: Exceptional communication and collaboration skills to effectively work with cross-functional teams, understand data requirements, and define data-related solutions.