Data Architect

Job Title: Data Architect
Location: Minneapolis, MN
Mode of Contract: C2C/W2

Role Summary

The Data Architect is responsible for designing, building, and governing scalable, secure, and high‑performance data architectures that support analytics, reporting, and advanced data use cases. This role works closely with business stakeholders, data engineers, analytics teams, and cloud/platform teams to ensure data solutions align with enterprise standards and business goals.

Key Responsibilities

• Design and own end‑to‑end data architecture, including data ingestion, transformation, storage, and consumption layers.
• Define data models (conceptual, logical, physical) for structured and semi‑structured data across enterprise platforms.
• Architect and oversee ETL / ELT pipelines handling large volumes of data from on‑prem and cloud sources.
• Define cloud‑based data platforms (Azure / AWS / Google Cloud Platform), including data lakes, warehouses, and lakehouse architectures.
• Ensure data quality, governance, security, and compliance through standards, policies, and best practices.
• Review and guide data engineering implementations; perform architecture and code reviews.
• Optimize performance, scalability, and cost of data solutions.
• Collaborate with stakeholders to translate business requirements into technical data solutions.
• Act as a subject matter expert (SME) for data architecture across programs and accounts.

Required Skills & Expertise

• Strong experience in Data Architecture and Data Integration Architecture.
• Advanced knowledge of data modeling, ETL/ELT design, and system architecture.
• Hands‑on experience with cloud data platforms (Azure preferred; AWS/Google Cloud Platform acceptable).
• Expertise in data warehousing concepts and modern lakehouse patterns.
• Strong understanding of large‑scale data processing and performance optimization.
• Experience working in Agile/Scrum delivery models.
• Excellent communication and stakeholder management skills.

Preferred / Nice‑to‑Have Skills

• Experience with Snowflake, Databricks, Azure Data Factory, StreamSets, or similar tools.
• Knowledge of Data Vault or other enterprise modeling techniques.
• Exposure to data visualization and analytics tools (Power BI, Tableau, etc.).
• Experience in regulated domains (Healthcare, BFSI, Insurance).
• Familiarity with DevOps / CI‑CD practices for data platforms.