Data Architect - Customer 360 (Remote - US)

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Architect - Customer 360 in the United States.

This role is designed for a hands-on data architect who will help define and build modern, cloud-based data architectures that enable self-service analytics and Customer 360 experiences. You will combine strategic architectural vision with technical expertise to design scalable data models, transformation frameworks, and unified data platforms. The position involves close collaboration with engineering, analytics, and business teams to standardize data practices, enforce governance, and deliver actionable insights. You will work with technologies such as Snowflake, dbt, Python, and modern orchestration tools, contributing to cloud modernization efforts and enterprise data initiatives. The environment is dynamic and collaborative, offering opportunities to influence enterprise-level solutions and make a measurable impact on business outcomes.

Accountabilities

• Design and implement data models (star, snowflake, and semantic) to support analytics and Customer 360 initiatives.
• Architect end-to-end data pipelines and transformation frameworks leveraging dbt and Python.
• Define and enforce standards for self-service analytics, enabling business users to access governed and reusable data assets.
• Partner with engineering, analytics, and business teams to align on data definitions, governance, and architecture best practices.
• Build and optimize data marts and semantic layers for BI tools such as Power BI or Looker.
• Guide the design and delivery of Customer 360 / Member 360 platforms, integrating multiple data sources into unified insights.
• Support cloud modernization efforts across Snowflake and BigQuery environments.
• Apply DevOps and CI/CD best practices using Git and orchestration frameworks such as Airflow or Dagster.

Requirements

• 10+ years of experience in data architecture or advanced data engineering roles.
• Strong hands-on expertise with Snowflake and/or BigQuery.
• Proficiency with dbt for modular data modeling, testing, and transformation.
• Solid Python skills for data processing and automation (e.g., Pandas, SQLAlchemy).
• Proven track record in designing self-service analytics platforms or Customer 360 data products.
• Knowledge of data governance, lineage, and metadata management practices.
• Familiarity with orchestration and CI/CD tooling such as Airflow, Dagster, or GitHub Actions.
• Experience in Financial Services or Life Sciences is highly preferred.
• Self-driven, detail-oriented, and capable of owning architectural solutions end-to-end.