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Sigmasoft - Data Architect - Snowflake DB

Sigmasoft Infotech Private Limited
Multiple Locations
13 - 15 Years
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3.9white-divider79+ Reviews

Posted on: 22/09/2025

Job Description

Data Architect (Snowflake)


About the Role :


We are seeking a skilled Data Architect (Snowflake) to design, implement, and optimize our cloud-based data architecture. In this role, you will be responsible for building scalable, high-performance data solutions using Snowflake and associated data ecosystem tools. You will play a critical role in defining data strategy, data modeling standards, and architecture best practices across the organization.

Key Responsibilities :


- Design and implement robust, scalable Snowflake-based data architectures.


- Lead the development and optimization of data models (both logical and physical) to support analytics, reporting, and operational workflows.

- Collaborate with data engineers, analysts, and stakeholders to translate business requirements into technical solutions.

- Establish and enforce data architecture standards, governance, and best practices.

- Design and implement data pipelines using ETL/ELT tools (e.g., dbt, Fivetran, Informatica, Talend, etc.).

- Optimize Snowflake performance through clustering, partitioning, caching, and query tuning.

- Define data security, access controls, and data masking strategies in Snowflake.

- Integrate Snowflake with various data sources (e.g., AWS, Azure, GCP, APIs, on-prem systems).

- Stay updated with Snowflakes evolving features and recommend adoption strategies.

Required Qualifications :


- Bachelors or Masters degree in Computer Science, Information Systems, or related field.


- Experience in data architecture, data engineering, or database development.

- Hands-on experience with Snowflake in production environments.

- Strong knowledge of data modeling (star/snowflake schemas) and dimensional modeling.

- Proficiency with SQL, Python, and ETL/ELT tools.

- Experience with cloud platforms (AWS, Azure, or GCP).

- Knowledge of data governance, data quality, and metadata management.


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