Snowflake Data Architect

Small Arc Inc

New York, NY, United States

3 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Application Programming Interfaces (APIs) Microsoft Azure Bash Shell Big Data Unix Cloud Computing Cloud Database Databases Data Architecture Extract Transform Load (ETL) Data Transformation Data Systems

+26 more

Data Vault Modeling Data Warehousing Database Queries Dimensional Modeling Python (Programming Language) PostgreSQL SQL Azure Performance Tuning Queueing Systems Windows Shell Azure Data Lake Shell Script SQL Databases Informix Data Storage Management Cloud Platform System Azure Data Factory Snowflake Data Lakes Pyspark Cosmos DB Data Management Physical Data Models Azure Synapse Analytics Data Pipelines Databricks

Job description

We are looking for a Snowflake Data Architect who will be responsible for designing a solution for a big retail company. The main focus is to support processing of big data volumes and integrate solutions to current architecture.

Requirements

Must have:

Overall years of experience required 12+ (at least 5+ years in an Architect position)
Strong, recent hands-on expertise with Azure Data Factory and Synapse is a must (6+ years).
Strong expertise in designing and implementing data models, including conceptual, logical, and physical data models, to support efficient data storage and retrieval.
Strong knowledge of Microsoft Azure, including Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory, and Azure Databricks, pySpark for building scalable and reliable data solutions.
Extensive experience with building robust and scalable ETL/ELT pipelines to extract, transform, and load data from various sources into data lakes or data warehouses.
Ability to integrate data from disparate sources, including databases, APIs, and external data providers, using appropriate techniques such as API integration or message queuing.
Proficiency in designing and implementing data warehousing solutions (dimensional modeling, star schemas, Data Mesh, Data/Delta Lakehouse, Data Vault)
Proficiency in SQL to perform complex queries, data transformations, and performance tuning on cloud-based data storages.
Experience integrating metadata and governance processes into cloud-based data platforms
Certification in Azure, Databricks, or other relevant technologies is an added advantage
Experience with cloud-based analytical databases.
Experience with Azure MI, Azure Database for Postgres, Azure Cosmos DB, Azure Analysis Services, and Informix.
Experience with Python and Python-based ETL tools.
Experience with shell scripting in Bash, Unix or windows shell is preferable.
Demonstrated ability to lead cross-functional engineering teams, define technical strategy and architecture, drive delivery of complex data platforms, mentor engineers, and effectively communicate with stakeholders at all organizational levels.