Snowflake Data Architect (with SQL & DBT Experience)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Snowflake Data Architect with SQL & DBT experience, offering a contract length of "unknown" and a pay rate of "unknown." Requires 8+ years in data engineering, strong Snowflake and SQL skills, and financial services experience preferred.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 18, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Unknown
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Houston, TX
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🧠 - Skills detailed
#Data Engineering #dbt (data build tool) #Leadership #Visualization #Data Modeling #Scala #"ETL (Extract #Transform #Load)" #GCP (Google Cloud Platform) #Tableau #DevOps #Automation #Microsoft Power BI #Compliance #BI (Business Intelligence) #AWS (Amazon Web Services) #Version Control #SQL (Structured Query Language) #Data Governance #Azure #Snowflake #Security #Cloud #Data Architecture #Data Science #Looker #Data Pipeline #Airflow #SQL Queries
Role description
Key Responsibilities
• Architect, design, and implement scalable data solutions leveraging Snowflake and DBT.
• Develop and optimize SQL queries, data models, and transformation pipelines.
• Collaborate with business stakeholders, analysts, and data scientists to translate requirements into efficient data solutions.
• Implement best practices for data governance, quality, security, and compliance.
• Monitor, troubleshoot, and enhance data pipelines for performance and reliability.
• Drive automation and CI/CD practices within the data engineering ecosystem.
• Provide technical leadership and mentorship to junior engineers where needed.
Required Skills & Experience
• 8+ years of experience in data engineering or data architecture roles.
• Strong hands-on expertise with Snowflake (data modeling, performance optimization, security, and integration).
• Proficiency in DBT for transformation and workflow management.
• Advanced knowledge of SQL (query optimization, complex joins, window functions, CTEs).
• Experience in data pipeline orchestration and integration tools (e.g., Airflow, Prefect, or similar).
• Solid understanding of ETL/ELT design patterns, data warehousing concepts, and modern data architectures.
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud Platform).
Nice to Have
• Previous experience working in the financial services domain (banking, insurance, capital markets, fintech).
• Exposure to data visualization or BI tools (Tableau, Power BI, Looker).
• Experience with version control, CI/CD, and DevOps practices for data.
• Strong problem-solving, analytical, and communication skills.
Key Responsibilities
• Architect, design, and implement scalable data solutions leveraging Snowflake and DBT.
• Develop and optimize SQL queries, data models, and transformation pipelines.
• Collaborate with business stakeholders, analysts, and data scientists to translate requirements into efficient data solutions.
• Implement best practices for data governance, quality, security, and compliance.
• Monitor, troubleshoot, and enhance data pipelines for performance and reliability.
• Drive automation and CI/CD practices within the data engineering ecosystem.
• Provide technical leadership and mentorship to junior engineers where needed.
Required Skills & Experience
• 8+ years of experience in data engineering or data architecture roles.
• Strong hands-on expertise with Snowflake (data modeling, performance optimization, security, and integration).
• Proficiency in DBT for transformation and workflow management.
• Advanced knowledge of SQL (query optimization, complex joins, window functions, CTEs).
• Experience in data pipeline orchestration and integration tools (e.g., Airflow, Prefect, or similar).
• Solid understanding of ETL/ELT design patterns, data warehousing concepts, and modern data architectures.
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud Platform).
Nice to Have
• Previous experience working in the financial services domain (banking, insurance, capital markets, fintech).
• Exposure to data visualization or BI tools (Tableau, Power BI, Looker).
• Experience with version control, CI/CD, and DevOps practices for data.
• Strong problem-solving, analytical, and communication skills.
