Snowflake Data Architect

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. You’ll collaborate with Product Owners, Data Architects, Analytics Engineers, and Platform teams to deliver reliable, scalable, and well-governed data solutions for TJX.

Snowflake Schema, DataArchitect Data Modeling Tool, Database Extract Transform and Load (ETL), Star Schema, Data Modeling, Information/Data Security (InfoSec), Performance Tuning/Optimization, SQL (Structured Query Language), DataArchitect Data Modeling Tool, Use Cases, 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 1/2; 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 & CI/CD: Git workflows, branching, code reviews, packaging, environment promotion.