Data Architect

We are seeking an experienced Data Architect to define and evolve enterprise data architecture and design scalable, secure, and high-performing data solutions aligned with business strategy.

The role will shape target-state architecture, platform capabilities, data patterns, and modernization roadmaps across data ingestion, storage, transformation, governance,h analytics, and AI consumption.

The ideal candidate combines deep architecture expertise with a strong understanding of Finance, Sales, or Operations. This role partners with Product, Engineering, Analytics, AI, and business leaders to establish architecture direction, guide solution design, and ensure the data platform remains reusable, interoperable, governed, and future-ready.

Key Responsibilities

Design Scalable Data Solutions

Architect end-to-end data solutions spanning ingestion, integration, transformation, storage, serving, analytics, and AI consumption. Define conceptual, logical, and physical data architectures and select appropriate patterns for batch, streaming, and near-real-time use cases. Ensure designs meet scalability, performance, resilience, availability, security, and disaster recovery requirements. Lead architecture reviews and guide engineering teams through solution implementation. Build and Evolve the Data Platform

Define target-state architecture for modern data warehouses, lakehouses, data lakes, and analytical platforms. Create platform blueprints, reference architectures, reusable patterns, and technology standards. Guide legacy modernization and migration to cloud-native, Snowflake-aligned architectures. Evaluate platform capabilities and recommend investments based on business value, interoperability, scalability, and cost. Drive Data Strategy and Collaboration

Translate business strategy into data capabilities, architecture roadmaps, and prioritized modernization initiatives. Partner with Product, Engineering, Analytics, AI, Security, and business leaders on architecture decisions. Communicate trade-offs, risks, dependencies, and recommendations to technical and executive stakeholders. Provide architecture leadership and mentor teams on patterns and design decisions. Ensure Standards and Innovation

Establish standards for data modeling, integration, metadata, lineage, quality, interoperability, security, and responsible data use. Ensure solution designs align with enterprise architecture, privacy, compliance, and governance principles. Evaluate emerging technologies in AI, automation, streaming, and cloud data platforms. Promote reusable data products, engineering excellence, and continuous architecture improvement., Revenue Analysis Budgeting Forecasting P&L Analytics Sales

Sales Operations Pipeline Analytics CRM Insights Revenue Growth Operations

Process Optimization Workforce Planning Productivity Operational Analytics Additional Experience

12+ years of experience in Data Engineering, Data Architecture, Data Warehousing, or Enterprise Architecture. Proven experience defining and implementing enterprise-scale data architectures and cloud data platforms. Experience leading modernization initiatives and architecture roadmaps across complex data ecosystems. Strong track record of designing solutions that support analytics, operational reporting, AI/ML, and business growth. Mandatory Skills

Enterprise and Solution Data Architecture Snowflake-aligned Platform Architecture Conceptual, Logical, and Physical Data Modeling Data Warehouse, Lakehouse, and Data Lake Architecture Batch, Streaming, Real-Time, API, and Event-Driven Integration Patterns Cloud Architecture on Azure, AWS, or Google Cloud Platform Metadata, Lineage, Data Quality, Privacy, and Governance Architecture Performance, Resilience, Availability, Disaster Recovery, and Cost Optimization Architecture Standards, Reference Patterns, Design Reviews, and Technology Evaluation Functional / Domain Experience, Executive stakeholder management Technical leadership and strategic roadmap development Ability to connect business strategy with target-state data capabilities and investment priorities Technical Skills

Snowflake Data Cloud architecture and solution design Enterprise data warehousing, lakehouse, data mesh, and data-product architectures Dimensional modeling, Data Vault, and semantic data models ELT/ETL, CDC, streaming, and data-pipeline architecture Snowpark using Python or SQL and Snowflake Cortex AI Performance engineering, workload management, and FinOps principles Data sharing, Snowflake Marketplace, and Native Applications GenAI, LLMs, RAG, vector search, and AI-ready platform architecture APIs, event-driven architecture, and microservices integration CI/CD, Infrastructure as Code, and Git Preferred Skills

Experience with enterprise data modernization and cloud migration programs. Experience designing AI/GenAI-ready data platforms. Strong understanding of data mesh and data product operating models. Experience with data cataloging and governance platforms. Experience with enterprise architecture frameworks and architecture governance. Strong communication, presentation, and stakeholder-management skills. Ability to work effectively with both technical and business leadership.