Enterprise Data Architect

Description

The Enterprise Data Architect is responsible for the strategic design, governance, and implementation of Rochester Electronics' enterprise data warehouse environment. This position plays a critical role in advancing the company's data modernization strategy by establishing a secure, scalable, and compliant Snowflake-based platform that unifies data across Manufacturing, Finance, Sales, and Engineering functions.

The Enterprise Data Architect will serve as the technical authority for data architecture, modeling, and governance, ensuring that enterprise data assets are well-structured, compliant with ITAR regulations, and optimized for analytics and AI-driven decision-making.

Responsibilities

• Data Architecture & Platform Design
  • Design and implement a Snowflake Enterprise Data Warehouse (EDW) using a medallion architecture (Bronze ? Silver ? Gold).
  • Define and maintain standards for schemas, naming conventions, data tagging, and database roles.
  • Implement RBAC frameworks, network policies, and resource monitors to ensure security, performance, and cost accountability.
  • Oversee the configuration and lifecycle management of dynamic tables, streams, and tasks supporting near real-time data refresh.
  • Manages platform implementations and upgrades efforts, and any IT-related user training.

• Governance & Compliance
  • Establish and maintain data governance frameworks aligned with ITAR and corporate data protection standards.
  • Implement masking policies, row-access policies, and sensitivity tagging for financial and restricted data.
  • Collaborate with Compliance, IT Security, and Audit teams to ensure traceability and documentation of all data lineage and access controls.
• Modeling & Data Standards
  • Develop and maintain Kimball-style dimensional models to support analytical use cases in Manufacturing, Finance, and Sales.
  • Define model grains, surrogate keys, and change tracking mechanisms (including Slowly Changing Dimensions Type II).
  • Standardize fact and dimension table structures for enterprise-wide consistency and cross-departmental integration.

• Integration & Automation
  • Partner with cross-functional analysts and developers to orchestrate automated data pipelines.
  • Manage service accounts, warehouses, and compute isolation for departmental workloads.
  • Develop and document automation scripts for key rotation, environment cloning, and metadata synchronization.

• Analytics Enablement
  • Collaborate with BI teams to build certified semantic models and Gold-layer views for Power BI and Tableau.
  • Enable data democratization through well-governed, reusable datasets and standardized KPI definitions.
  • Support the integration of AI and machine learning initiatives through secure data provisioning and feature store development.
  • Work with developers, managers, support and service providers to maximize the effectiveness of the EDW.

• Leadership & Collaboration
  • Serve as a technical liaison among Finance, Manufacturing, and Sales departments.
  • Mentor analysts and engineers on Snowflake best practices, dimensional modeling, and secure data design. Provide executive reporting and documentation on data platform adoption, performance, and cost optimization.
  • Provide strong leadership and guidance while working with others specifically related to the IT applications department, project managers and project teams.
  • Coordinates with different departmental teams to produce better business outcomes.
  • Influences stakeholders to support business projects.
  • Provides data-driven advice on how to expand or refine its operations to meet company needs.
  • Manages smaller side projects as assigned to evaluate vendors, tools, and new technologies. e.g. document control, dashboard and reporting tools, imaging solutions, interfaces, IoT, etc.
  • Consult with managers to determine what role the EDW impacts the business.

Qualifications

• Minimum requirement of bachelor's degree in computer science, Data Engineering, or related discipline
• 7+ years of professional experience in data architecture, data engineering, or analytics engineering roles
• 3+ years of hands-on experience with Snowflake (RBAC, masking policies, dynamic tables, resource monitors)
• Proficiency in SQL and data transformation frameworks such as dbt
• Strong knowledge of Kimball dimensional modeling and data warehouse design patterns
• Experience integrating with ERP and MES systems such as Epicor and Camstar
• Familiarity with Power BI, Tableau, or equivalent BI tools
• Working knowledge of data privacy and compliance frameworks (ITAR, SOX, GDPR, etc.)
• Prefer experience with Snowpark or machine learning data pipelines
• Familiarity with SQLFluff or automated SQL linting/validation tools
• Strong understanding of cost governance and monitoring in Snowflake
• Excellent communication and documentation skills, with the ability to bridge business and technical audiences