Snowflake Solution Architect

Tredence Inc.; Austin (TX); On-site; USD 160,000 - 240,000; Full time

Job summary

Tredence Inc. in Austin, TX is seeking a highly technical Snowflake Solution Architect to lead enterprise data estate design for sales planning and financial forecasting.

You will be the technical authority for the Snowflake AI Data Cloud, architecting cost‑aware, secure, high‑concurrency platforms that ingest and transform feeds from Oracle Demantra, Anaplan, Hyperion, SAP and Salesforce. You will drive AI‑accelerated engineering with Snowflake CoCo, Snowpark, Dynamic Tables, Cortex AI, and

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or a related technical discipline.
• 5+ years hands‑on experience as a technical architect designing enterprise platforms on Snowflake Data Cloud.
• 10+ years in data platform engineering, enterprise software architecture, and solution design across cloud environments (AWS, Azure, GCP).
• Expert‑level mastery of Snowflake ecosystem components: Snowpark, Dynamic Tables, Streams & Tasks, Snowpark Containers, CoCo, Cortex AI, Horizon.
• Deep proficiency in SQL, Python, dbt, Data Vault 2.0, Kimball dimensional modeling, and API‑based data ingestion frameworks.

Responsibilities

• End‑to‑End Technical Architecture: Design and deploy multi‑region Snowflake data architectures for FP&A, sales planning, and forecasting analytics.
• Storage & Compute Strategy: Define warehouse sizing, auto‑scaling, and storage strategies including Hybrid Tables and Apache Iceberg.
• Advanced Pipeline & Orchestration Architecture: Build ELT pipelines with Dynamic Tables, Streams & Tasks, Snowpark for declarative data processing.
• Application & Solution Delivery: Architect write‑back capabilities and REST APIs for financial planning interfaces.
• AI‑Native Engineering: Lead Snowflake CoCo adoption across Snowsight, CoCo Desktop, and CLI to accelerate modeling and SQL optimization.

Skills

Solution Architecture Leadership

Technical Communication

Performance Tuning

FP&A and forecasting analytics

SQL/Python/dbt

Education

Bachelor’s or Master’s degree in CS/SE or related

Tools

Snowflake Data Cloud

Snowpark

Dynamic Tables

Cortex AI

Snowflake Horizon

Apache Iceberg

Job description

We are seeking a highly technical, hands‑on Snowflake Solution Architect with deep expertise in cloud data platform architecture, solution design, and AI‑accelerated engineering to lead the design and implementation of our enterprise Sales Planning & Financial Forecasting data estate.

In this role, you will be the primary technical authority for our Snowflake AI Data Cloud ecosystem. You will architect high‑performance, cost‑optimized, and secure data platform solutions that ingest, transform, and serve complex planning and forecasting workloads (integrating source feeds from engines such as Oracle Demantra, Anaplan, Hyperion, SAP, and Salesforce). You will leverage modern Snowflake capabilities—including Snowflake CoCo (AI coding agent), Snowpark, Dynamic Tables, Cortex AI, Hybrid Tables, and Snowflake Horizon—to design next‑generation data architectures for financial forecasting, demand sensing, and scenario modeling.

Key Responsibilities

Role description

Position Overview

Location - Austin, TX

We are seeking a highly technical, hands‑on Snowflake Solution Architect with deep expertise in cloud data platform architecture, solution design, and AI‑accelerated engineering to lead the design and implementation of our enterprise Sales Planning & Financial Forecasting data estate.

In this role, you will be the primary technical authority for our Snowflake AI Data Cloud ecosystem. You will architect high‑performance, cost‑optimized, and secure data platform solutions that ingest, transform, and serve complex planning and forecasting workloads (integrating source feeds from engines such as Oracle Demantra, Anaplan, Hyperion, SAP, and Salesforce). You will leverage modern Snowflake capabilities—including Snowflake CoCo (AI coding agent), Snowpark, Dynamic Tables, Cortex AI, Hybrid Tables, and Snowflake Horizon—to design next‑generation data architectures for financial forecasting, demand sensing, and scenario modeling.

Key Responsibilities

1. Core Snowflake Platform Architecture & Solution Design

• End-to-End Technical Architecture: Design and deploy enterprise‑grade, multi‑region Snowflake data architectures aligned with the Snowflake Well‑Architected Framework (WAF) to support high‑concurrency FP&A, sales planning, and demand forecasting analytics.
• Storage & Compute Strategy: Define optimal warehouse sizing, auto‑scaling multi‑cluster configurations, query acceleration, search optimization services, and storage strategies incorporating native tables, Hybrid Tables (Unistore), and Apache Iceberg open storage formats.
• Advanced Pipeline & Orchestration Architecture: Architect robust ELT pipelines leveraging Dynamic Tables, Streams & Tasks, and Snowpark (Python/Scala/Java) for declarative data processing, near‑real‑time synchronization, and complex time‑series aggregation.
• Application & Solution Delivery: Architect write‑back capabilities and custom financial planning interfaces using Streamlit in Snowflake (SiS), native stored procedures, and REST APIs.

2. AI‑Accelerated Engineering & Snowflake CoCo Integration

• AI‑Native Engineering Workflows: Lead the adoption of Snowflake CoCo (formerly Cortex Code) across Snowsight, CoCo Desktop, and CLI environments to accelerate data model prototyping, pipeline creation, dbt project generation, and SQL optimization.
• Agentic Frameworks & Cortex AI: Architect intelligent conversational agents and analytics tools using Cortex AI, Cortex Search, and the CoCo Agent SDK, enabling FP&A and sales planning teams to perform natural‑language query analysis, variance root‑cause analysis, and automated scenario modeling.
• Automated Architecture Assessments: Utilize Snowflake CoCo skills to execute automated Well‑Architected reviews, health checks, and continuous code quality audits across Snowflake environments.

3. Data Modeling

• Scalable Data Modeling: Design highly performant data models (Kimball Dimensional, Data Vault 2.0, and Real‑Time Operational Data Stores) specifically structured for deep hierarchy traversal, financial roll‑ups, multi‑currency conversions, and territory re‑alignments.

4. Enterprise Governance, Security & FinOps

• Snowflake Horizon Governance: Implement zero‑trust security and data governance policies using Snowflake Horizon, including Role‑Based Access Control (RBAC), Attribute‑Based Access Control (ABAC), Dynamic Data Masking, Row Access Policies, and Tag‑Based Masking.
• FinOps & Resource Optimization: Establish platform cost control guardrails, budget s, resource monitors, and query performance tuning, leveraging CoCo governance frameworks and system usage views to optimize credit consumption across virtual warehouses and AI features.

Required Qualifications

Technical & Architectural Expertise

• Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or a related technical discipline.
• Snowflake Mastery: 5+ years of hands‑on experience as a technical architect designing, building, and optimizing enterprise platforms on the Snowflake Data Cloud.
• Data Platform & Solution Design: 10+ years in data platform engineering, enterprise software architecture, and solution design across cloud environments (AWS, Azure, or GCP).
• Snowflake Ecosystem Components: Expert‑level mastery of:
• Snowpark (Python/Java/Scala) and Snowpark Container Services (SPCS).
• Dynamic Tables , Streams, Tasks, and event‑driven data pipelines.
• Snowflake CoCo (Cortex Code) for AI‑driven development, CLI automation, and agent building.
• Cortex AI functions, Cortex Search, and Streamlit in Snowflake.
• Snowflake Horizon security controls (RBAC, Row Access Policies, Data Masking).
• Data Modeling & Engineering: Deep proficiency in SQL, Python, dbt, Data Vault 2.0, Kimball dimensional modeling, and API‑based data ingestion frameworks.

Key Competencies

• Solution Architecture Leadership: Ability to take vague business requirements and convert them into concrete, well‑architected, and scalable Snowflake design patterns.
• Technical Communication: Excellent technical design documentation skills (data flow diagrams, architecture blueprints, security topologies) and executive presentation abilities.
• Performance Tuning: Advanced skills in analyzing Query Profiles, micro‑partitioning, clustering keys, search optimization, and resolving data skew issues.