Snowflake Architect

Snowflake Architect

Location: Anywhere in the US

Experience: 15–18+ years, including 5+ years in Snowflake architecture, Customer consulting, solution design, and enterprise data platform engineering

Employment Type: Full-Time

About Mastech Digital

www.mastechdigital.com

Mastech Digital is a leading Data Engineering, Analytics, and AI solutions company helping enterprises modernize their data ecosystems and unlock business value through advanced analytics, cloud platforms, and AI-driven innovation. Our teams of architects, engineers, and data specialists collaborate to deliver scalable, future-ready solutions for global enterprises across industries, including BFSI, Retail, Industrial, Energy, and Health & Life Sciences.

Role Overview

We are seeking a strategic, advisory and hands-on Snowflake Architect to design enterprise-grade Snowflake Data Cloud platforms that support analytics, data engineering, governed data sharing, and AI/GenAI workloads. This is a senior architecture role for a highly skilled professional who can combine deep Snowflake expertise with strong data engineering, cloud architecture, governance, and AI-ready platform design capabilities.

The architect will define reference architectures, guide modernization and platform conversion programs, establish reusable engineering patterns, mentor teams, and advise business and technology stakeholders on secure, scalable, cost-efficient, and AI-ready Snowflake ecosystems.

Key Responsibilities

Snowflake Platform Architecture

• Define target-state Snowflake architecture across ingestion, storage, transformation, semantic consumption, governance, observability, and AI enablement.

• Design enterprise-scale Snowflake platforms using virtual warehouses, workload isolation, resource monitors, micro-partitioning, clustering strategies, caching, Time Travel, zero-copy cloning, secure data sharing, and cost governance patterns.

• Establish reusable reference architectures for analytics, data products, data engineering, semantic layers, and AI-ready data platforms.

• Develop logical and physical data models aligned to business domains, analytical use cases, data products, and performance requirements.

Data & AI Platform Enablement

• Architect AI-ready data foundations for analytics, ML, GenAI, semantic search, conversational analytics, and governed retrieval-augmented generation use cases.

• Evaluate and design solutions using Snowflake Cortex AI, Cortex Search, Cortex Analyst, Document AI, Snowpark, Snowpark ML, and Snowflake-native AI functions where appropriate.

• Design patterns for embeddings, vector search, semantic models, feature engineering, context preparation, and secure AI access to enterprise data.

• Work with business, data, AI, and engineering stakeholders to convert AI use cases into governed, scalable Snowflake platform patterns.

Modernization & Platform Conversion

• Lead assessment, design, and execution of legacy data platform modernization and conversion programs to Snowflake from platforms such as Teradata, Oracle, Netezza, SQL Server, Hadoop, Redshift, Synapse, or equivalent enterprise systems.

• Define coexistence, transition, validation, reconciliation, cutover, rollback, and operational readiness patterns for enterprise-scale platform programs.

• Architect modern ELT/ETL and CDC pipelines using Snowpipe, Snowpipe Streaming, Streams, Tasks, Dynamic Tables, external stages, dbt, orchestration frameworks, and cloud-native services.

Governance, Security, Performance & Operations

• Define enterprise-grade governance using RBAC, masking policies, row access policies, object tagging, classification, lineage, access history, auditability, and compliance-ready controls.

• Optimize Snowflake workloads through query profiling, warehouse right-sizing, materialization strategy, clustering, partition pruning, cache utilization, and compute cost controls.

• Establish monitoring, observability, data quality, reliability, incident response, release management, and operational excellence standards.

• Design secure integration patterns across AWS, Azure, GCP, BI tools, data engineering platforms, APIs, and enterprise identity systems.

Architecture Leadership & Strategic Engagement

• Partner with business leaders, client stakeholders, product owners, and engineering teams to define Snowflake Data Cloud strategies and solution roadmaps.

• Lead architecture workshops, technical discovery sessions, solution reviews, executive presentations, and proposal solutioning for strategic opportunities.

• Mentor architects, data engineers, analytics engineers, and developers on Snowflake engineering standards and platform best practices.

• Build accelerators, reusable frameworks, architecture blueprints, decision records, and Snowflake Studio assets.

Required Qualifications

• 15–18+ years of experience in data architecture, data engineering, analytics architecture, cloud data platforms, or enterprise data modernization.

• 5+ years of hands-on Snowflake architecture and implementation experience, including production-grade enterprise platform design.

• Deep expertise in Snowflake architecture, including virtual warehouses, micro-partitioning, clustering, caching, Time Travel, zero-copy cloning, secure data sharing, Snowpipe, Streams, Tasks, Dynamic Tables, external tables, Iceberg Tables, Snowpark, and cost optimization.

• Strong understanding of Snowflake security and governance, including RBAC, network policies, masking policies, row access policies, tags, classification, access history, lineage, and audit controls. • Strong SQL and Python skills, with hands-on experience building scalable data engineering, transformation, and automation frameworks.

• Hands-on experience with dbt or equivalent transformation frameworks, orchestration tools, CI/CD practices, Git-based development, and DataOps standards.

• Experience designing dimensional, Data Vault, lakehouse, semantic layer, and data product architectures for enterprise analytics and BI consumption.

• Experience enabling analytics, BI, ML, GenAI, or AI-ready data platform workloads on modern cloud data platforms.

• Strong knowledge of AWS, Azure, or GCP data services and secure cloud integration patterns.

• Excellent executive communication, consulting, stakeholder management, and technical leadership skills.

Preferred Qualifications

• SnowPro Advanced Architect certification preferred; SnowPro Core certification strongly valued.

• Experience with Snowflake Cortex AI, Cortex Search, Cortex Analyst, Document AI, Snowpark ML, AI Functions, or ML/GenAI integration patterns.

• Experience with vector search, embeddings, semantic search, RAG architecture, AI observability, model evaluation, or responsible AI controls.

• Exposure to Snowflake Native Apps, Marketplace, secure data sharing, Iceberg Tables, open table formats, and cross-cloud data collaboration patterns.

• Experience with Databricks, Spark, Kafka, Airflow, Fivetran, Matillion, Coalesce, Terraform, or equivalent data engineering ecosystem tools.

• Experience contributing to Snowflake Studio, reusable accelerators, solution assets, pre-sales architecture, or enterprise advisory engagements.

• Domain exposure in one or more Mastech Digital focus verticals—BFSI, Retail, Industrial, Energy, or Health & Life Sciences—is an added advantage.

What Makes You Successful

• You can balance strategic architecture thinking with hands-on technical depth in Snowflake, SQL, Python, and modern data engineering practices.

• You understand how to build secure, governed, performant, and cost-efficient Snowflake platforms for enterprise-scale workloads.

• You can translate business, analytics, and AI requirements into practical platform architecture patterns and delivery roadmaps.

• You are comfortable advising senior stakeholders while mentoring engineering teams and raising architecture quality across the organization.

Why Join Mastech Digital?

• Work on strategic Snowflake Data Cloud, Data Engineering, Analytics, and AI platform initiatives.

• Work with Customers on providing advisory on building AI ready Data foundation

• Shape enterprise modernization and platform conversion programs for global clients.

• Influence next-generation data and AI architecture strategies across industries.

• Contribute to reusable Snowflake accelerators, architecture blueprints, and innovation-led solution assets.