Amazon Simple Storage Service (S3), Amazon Web Services (AWS), Architectural Analysis, Architectural Design, Caching, Cloning, Cloud Computing, Code Reviews, Continuous Deployment/Delivery, Continuous Integration, Cost Control, Data Analysis, Data Management, Data Modeling, Data Quality, Data Warehousing, DataArchitect Data Modeling Tool, Database Extract Transform and Load (ETL), Database Technology, Dimensional Modeling, GCP (Good Clinical Practices), Git, Information/Data Security (InfoSec), Microsoft Windows Azure, Performance Tuning/Optimization, Python Programming/Scripting Language, SQL (Structured Query Language), Service Level Agreement (SLA), Snowflake Schema, Source Code/Configuration Management (SCM), Star Schema, Use Cases
Role
Snowflake Data Architect
Location
Boston, MA
Onsite
Type
Contract
Role Summary
We are seeking a hands-on Snowflake Data Architect to design, build, optimize, and productionize data pipelines and data products on Snowflake for enterprise analytics use cases. The role requires deep expertise in SQL, ELT, ETL orchestration, data modeling, 3NF, Star, Snowflake performance tuning, cost optimization, and secure data sharing in Snowflake. Youll collaborate with Product Owners, Data Architects, Analytics Engineers, and Platform teams to deliver reliable, scalable, and well-governed data solutions for TJX.
Required Skills & Experience
Must have:
- Snowflake Hands-on Expert
- Warehouses, Databases, Schemas, Roles & Grants, RBAC
- Stages (internal, external)
- File Formats (COPY INTO, Snowpipe)
- Streams & Tasks
- Time Travel
- Cloning
- Zero-Copy Clones
- Fail-safe awareness
- Query tuning
- Clustering keys
- Micro-partitions
- Caching
- Pruning
- Secure data sharing
- Masking policies
- Tags
- Governance features
- BCR
- DR
- Storage integration and Parameters
- Materialized Semantic Views
- Dynamic Tables
- Stream Lit
- Snowflake Architecture
- SQL Mastery
- Strong production-grade SQL for large-scale transformations
Good to have:
- Programming (Python preferred for ELT utilities framework integration data quality checks)
- dbt for transformation-as-code is a strong plus
- Orchestration (Airflow preferred or ADF/Glue/Composer scheduling dependencies retry policies SLAs)
- Data Modeling (Dimensional modeling, Kimball, SCD Type 12 normalization/denormalization trade-offs exposure to data vault is a plus)
- Cloud Platforms (Experience with at least one major cloud AWS/Azure/GCP for storage S3/ADLS/GCS IAM networking basics and secrets management)
- Version Control & CICD (Git workflows branching code reviews packaging environment promotion)
- Data Quality (Testing frameworks dbt tests Great Expectations and monitoring/observability)
P
PROLIM Global Corporation