Sr Data Architect

We are looking for a Sr Data Architect who will perform mission critical duties in our data engineering strategy, contributing to and leading the development of our Enterprise Data and Analytics Platforms. A passionate professional who can blend the ever-evolving technology landscape of Cloud and Advanced Analytics with responsibilities to provide input on implementation and administration methodologies to management.

The Sr Data Architect will mainly be responsible to develop, optimize and oversee company’s logical, conceptual, and physical data model and provide recommendations. This role will be responsible for expanding, optimizing, and monitoring our expanding data pipelines through meticulous architecting, intelligent business logic, consistent data governance, testing and continuous delivery.

Responsibilities

• Extensive experience with designing and implement scalable data architectures using Snowflake and Azure services.
• Experience with developing and maintaining robust ETL pipelines to integrate data from various sources into Snowflake.
• Must have experience with DBT.
• Deep understanding of relational as well as NoSQL data stores, methods and approaches (star and snowflake, dimensional modelling).
• Experience with data security and data access controls and design in Snowflake.
• Proficiency in complex SQL, Unix Shell/Python Scripting, performance tuning and database optimization techniques.
• Must have expertise in Azure Platform as a Service (PAAS) model and its integration with Snowflake to load/unload data.
• Implement cloud-based Enterprise data warehouse solutions with multiple data platforms along with Snowflake and NoSQL environment to build data movement strategy.
• Lead in Developing Project requirements for end-to-end.
• Make necessary on-going updates to modeling principles, processes, solutions, and best practices to ensure that the Snowflake is aligned with business needs of the environment. 
• Act as Data domain expert for Snowflake in a collaborative environment to provide demonstrated understanding of data management best practices and patterns.
• Implement and enforce data governance policies, ensuring data quality, security, and compliance.
• Work closely with data scientists, analysts, and other stakeholders to understand data needs and deliver solutions.
• Ability to work with business team and help them gathering all requirements based on data.

Requirements

• 10+ years of experience implementing data management solutions (Required).
• Technology management consulting experience (Highly Desired).
• Deep understanding of Snowflake architecture, features, and best practices. 
• Expertise in Snowflake concepts like setting up Resource monitors, RBAC controls, scalable virtual warehouse, SQL performance tuning, zero copy clone, time travel and automating them. 
• Experience in handling unstructured, structed, semi-structured data.
• Experience in Migration processes to Snowflake from on-premises database environment. 
• Experience in designing and building manual or auto ingestion data pipeline using Snowpipe.
• Experience in Cloud technologies such as Azure Components, Azure Data Factory, Dbt.
• Design and develop automated monitoring processes on Snowflake using combination of Dbt, Snowflake and Azure Data Factory.
• Experience in developing stored Procedures writing Queries to analyze and transform data. 

Education:

• Bachelor’s Degree: A degree in Computer Science, Information Technology, Data Science, or a related field is usually required.
• Master’s Degree (Optional): A master’s degree in a related field can be advantageous and sometimes preferred for senior roles.

Certifications (Optional but Beneficial):

• Snowflake Certifications: Certifications such as Snowflake SnowPro Core Certification can validate expertise in Snowflake.
• Azure Certifications: Certifications like Microsoft Certified: Azure Data Engineer Associate or Microsoft Certified: Azure Solutions Architect Expert.
• Other Relevant Certifications: Certifications in related areas such as data science, big data, or other cloud platforms.