Snowflake Architect

HCLTech•Union Beach, NJ

About The Position

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.

Requirements

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.

Responsibilities

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.
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.
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).
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.
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).
Lead technical discovery, translate business needs into architecture, and produce design artifacts (HLD/LLD, roadmaps, standards).
Mentor engineers, enforce engineering standards, and collaborate across product, platform, security, and operations teams.