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# Snowflake Solutions Architect

- **Company:** Tror AI for everyone
- **Location:** Union Beach, NJ, United States
- **Experience:** Expert
- **Salary:** $135,000.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Amazon S3, Data Analysis, Architectural Patterns, Business Intelligence Development, Data as a Services, Information Engineering, Data Files, Data Infrastructure, Extract Transform Load (ETL), Data Security, Dimensional Modeling, Python (Programming Language), Meta-Data Management, Performance Tuning, Query Optimization, Power BI, Cloud Services, Standard Sql, Salesforce.Com, SAP (Applications), SQL Databases, Systems Integration, Snowflake, Kubernetes, AWS Data Analytics, Data Management
- **Published:** August 1, 2026
- **Apply:** https://www.careerjet.com/jobad/us00ffb8660b16aff7df6d79ddfba17458

## About the Role

Snowflake: architecture patterns, security/governance, optimization, and operational best practices.
AWS Data Analytics Services: working knowledge of how services integrate for governed access (Lake Formation with Athena/Glue/Redshift/EMR).
Power BI: semantic model/dataset design and governance; ability to align BI layer with enterprise BI architecture principles.
Amazon Bedrock: ability to solution GenAI workloads using Agents/Knowledge Bases and implement guardrails for safety.
Strong SQL and data modeling (dimensional modeling, marts, analytical patterns).
Years of Experience Required > 10 Years
Mandatory Skills
Snowflake Admin, DBT Admin, Solution Architect, Python, SQL, AWS, 10+ years in data platform / analytics architecture (or equivalent depth in engineering + architecture).
Proven architecture experience with Snowflake (warehouse design, data modeling, performance tuning, governance/security).
Strong hands-on AWS analytics/data services experience, especially integrating lake + warehouse and enabling governed access.

## Description

We are seeking a hands-on Snowflake Solutions Architect to design and lead modern, scalable data platforms on Snowflake + AWS Analytics services, enable governed analytics through Power BI semantic models, and accelerate GenAI use cases using Amazon Bedrock (Agents/Knowledge Bases/Guardrails). The role will partner with business and engineering teams to define architecture, guide implementation, and ensure security, performance, and cost-efficiency across the data and AI landscape.
Key Responsibilities
1) Solution Architecture (Snowflake + AWS Analytics)
Own end-to-end architecture for cloud data platforms leveraging Snowflake and AWS-native analytics services (e.g., S3, Glue, Lake Formation, Athena, Redshift, EMR/Kinesis/MSK as applicable).
Define target-state patterns for historical + incremental loads, batch/real-time ingestion, and scalable transformations using tools like dbt and orchestration frameworks (e.g., Airflow).
Design Lakehouse / Medallion style architectures and integration approaches between AWS data lake and Snowflake analytics marts, including modern table formats (e.g., Iceberg where applicable).
Lead architecture reviews, trade-off decisions (performance/cost/security), and ensure solutions meet non-functional requirements.
2) Data Engineering Enablement & Integration
Guide teams on building robust ELT/ETL pipelines, metadata management, and data quality controls (audit, reconciliation, balance/control frameworks).
Establish best practices for Snowflake performance tuning, query optimization, and workload management.
Define ingestion patterns from enterprise sources (e.g., SAP and other systems) into AWS/Snowflake using standard integration approaches
3) Analytics & BI (Power BI)
Architect and govern Power BI semantic models/datasets, ensuring consistent metrics ("single version of truth"), strong performance, and reusability.
Implement enterprise-grade security for BI (e.g., Row-Level Security (RLS), access controls, dataset governance) aligned with data platform security design.
Partner with BI developers and stakeholders to deliver scalable reporting patterns and lifecycle governance (certification, promotion, workspace standards).
4) GenAI Architecture (Amazon Bedrock)
Design GenAI solution patterns using Amazon Bedrock, including Agents, Knowledge Bases (RAG), and safe deployment controls using Guardrails.
Define agent tool/action patterns (action groups), retrieval grounding strategy, and observability/tracing for production readiness.
5) Security, Governance & Compliance
Implement fine-grained access control across the lake/warehouse ecosystem and enforce governance controls for data access and auditability.
Define governance integration approaches beyond native capabilities when needed (catalog/lineage tools, stewardship workflows).
6) Stakeholder Leadership & Delivery
Lead technical discovery, translate business needs into architecture, and produce design artifacts (HLD/LLD, roadmaps, standards).
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