Jobs and Careers

Data Architect

Bridgewater, United Statesfull_timeVerifiedPosted 16 Mar 2025

About the role

Role: Data Architect (Snowflake)
Location: Bridgewater, NJ office (Hybrid/onsite)
Long term role

Day to day responsibilities:

Responsible for designing, implementing, and managing a data architecture strategy utilizing the Snowflake cloud data platform, ensuring data is accessible, secure, and optimized for analytics by collaborating with stakeholders to understand business needs, translating them into technical data models, and overseeing the development of data pipelines within the Snowflake environment; key duties include defining data governance policies, optimizing data storage and processing, and staying current with Snowflake features and best practices to deliver efficient data solutions.
Develop and maintain a comprehensive data architecture on Snowflake, including logical and physical data models, considering data ingestion, transformation, and access requirements.
Collaborate with business stakeholders to understand data needs, identify key performance indicators (KPIs), and translate them into actionable data solutions on Snowflake.
Design and implement data quality rules, data reconciliation observability, using data quality tools like Talend, ensuring data integrity, consistency, and reporting accuracy
Establish data governance policies and standards to ensure data quality, security, and compliance within Snowflake and Talend
Integrate Snowflake with other cloud services and platforms to facilitate data sharing and analysis across the organization.
Monitor and optimize query performance and manage workloads to ensure efficient and cost-effective data processing.

What you will bring:

Advanced SQL knowledge for data manipulation, querying, and data analysis.
Proficiency in one of the scripting languages such as Python or JavaScript for automating tasks and integrating Snowflake with other tools and services.
Expertise in designing and implementing dimensional and normalized data models.
Strong understanding of data warehousing principles and concepts.
Expertise with cloud platforms like AWS, Azure, or GCP. Experience with data integration tools like Talend, AWS Glue
Ability to effectively communicate technical concepts to both technical and non-technical stakeholders.