Job Title: Snowflake Data Architect
POSITION TYPE: Contract (5 months - Possible contract to hire)
LOCATION: Hybrid - Dallas, TX
Position Overview
14 years + Experience in Snowflake, SQL, AWS Data (Sage maker, Glue, Kinesis) and Cloud Data Engineering. As a Snowflake Data Architect (EA), you will be the strategic glue between business goals and IT execution for all Data engineering efforts. Your role is to design, implement, and optimize a high-performance data warehouse environment (Snowflake, Databricks, AWS) that serves as the "single source of truth." You won't just be moving data around; you'll be architecting a scalable foundation that enables real-time analytics, data sharing, and AI-driven insights across the enterprise. Your mission is to ensure that our technology data stack is scalable, secure, and—most importantly—aligned with where the company wants to be in five years.
Key Responsibilities
- Architecture Design: Design end-to-end data architectures within Snowflake, utilizing Virtual Warehouses, multi-cluster environments, and specialized storage optimization.
- Data Modeling: Create and maintain complex data models (Star Schema, Snowflake Schema, Data Vault 2.0) tailored for cloud-native performance. Strong Collaboration with various IT and Business stakeholders to curate, document and implement Data lineage, knowledge graphs, Data tracing and Compliance KPIs.
- Pipeline Engineering: Architect robust ETL/ELT pipelines using Snowpipe, Tasks, and Streams, integrating with tools like airbyte, dbt, Fivetran, or AWS.
- Governance & Security: Implement Role-Based Access Control (RBAC), data masking, and row-level security to ensure compliance with global standards (GDPR, HIPAA, etc.).
- Performance Tuning: Monitor and optimize query performance and credit consumption—ensuring the system is as cost-effective as it is fast. Expert-level SQL and deep knowledge of Snowflake-specific features (Time Travel, Zero-copy Cloning, Data Sharing etc.
- Snowflake Reference Designs: Implement reference designs for ETL/ELT pipeline engineering including integration efforts with AWS platforms.
- Data Governance: Setup architecture and governance standards from Data engineering and Platform perspective and enforce Data Lineage, Data Stewardship across all business units.
Required Qualifications
- 14+ years in IT, with 5-7 years in a formal progressive Data Architecture role.
- Mastery of cloud ecosystems (AWS/Azure), microservices, Data standards, IT Governance, Security Architecture, Architecture Guidance, Security and data integration patterns. 7+ years in Data Engineering, with 3+ years focused specifically on Snowflake implementations.
- Proficiency in Data Platforms – Snowflake, Microsoft SQL, Postgres, Databricks, Microsoft Power BI, Tableau Reporting, AWS Data (Sagemaker, Glue, Kinesis, RDS), Python, JavaScript, Scala, Go and Java programming.
- High-level "influencing without authority" and the ability to explain complex data engineering tech to non-techies.
- Snowflake Core Pro and Snowflake Advanced Architect Certifications(mandatory), Databricks (optional), AWS Data Engineering Certifications (mandatory), AWS Solution Architect Pro (nice to have)
- Bachelor’s or Master’s in CS, MIS, Data Science, MBA or a related field (or equivalent battle-hardened experience).