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Data Engineer - Remote

Roles & Responsibilities

  • Proven experience designing, building, and deploying enterprise data platforms, preferably using Snowflake
  • Strong expertise in ETL/ELT development, data modeling, schema design, RBAC, and data security
  • Experience integrating data from multiple enterprise systems (e.g., CRM, portfolio management, financial planning, custodial platforms) and implementing data governance, validation, monitoring, and auditing
  • Ability to collaborate with internal IT teams and external Snowflake implementation partners, and stay current with Snowflake ecosystem and cloud data engineering best practices

Requirements:

  • Collaborate with EP Wealth’s Snowflake implementation partner to design, configure, and deploy the firm’s first enterprise data platform
  • Develop and maintain secure, scalable ETL/ELT pipelines and Snowflake data models, schemas, and RBAC to support analytics and reporting
  • Implement data validation, monitoring, auditing, governance standards, and optimize Snowflake performance and cost while ensuring data quality
  • Work with stakeholders across IT and business teams to align technical design with business strategy, assist with data migrations and production rollout, and drive data-driven decision-making

Job description

EP Wealth Advisors (EPWA) is a wealth management advisory firm with over $42.2 billion as of December 31, 2025, serving predominately high net worth individuals. EPWA fosters an inclusive environment that offers opportunities for our associates to learn, grow and enhance their skills to take on new challenges to progress in their professional careers.

EP Wealth Advisors is launching its first enterprise data platform initiative, a strategic effort to build a modern, cloud-based data environment powered by Snowflake. As a Data Engineer, you will play a pivotal role in the design, development, and implementation of this platform — working in close partnership with both internal technology teams and an experienced Snowflake implementation service provider.

This position is ideal for a data professional who thrives in a collaborative, fast-paced environment and wants to contribute to building a foundational data infrastructure from the ground up. You will help establish best practices, design scalable pipelines, and ensure the new platform enables firmwide analytics, reporting, and data-driven decision-making.

Salary Range: $120,000 - $150,000 plus annual bonus 

Duties and Responsibilities:

• Collaborate closely with EP Wealth’s Snowflake implementation partner to design, configure, and deploy the firm’s first enterprise data platform.

• Participate in architecture design sessions, technical planning, and milestone reviews with both internal stakeholders and external partners.

• Develop and maintain efficient, secure, and scalable ETL/ELT data pipelines to ingest data into Snowflake.

• Build and optimize Snowflake data models, schemas, and role-based access controls.

• Define and enforce Snowflake best practices for performance optimization, cost management, and data security.

• Support environment setup, data migration, and initial production rollout activities in coordination with the implementation partner.

Integrate data from multiple enterprise systems including CRM, portfolio management, financial planning, and custodial platforms

• Design data models and reusable ingestion frameworks that support analytics and reporting use cases.

• Contribute to the development of a unified enterprise data model and metadata framework.

• Collaborate with the implementation partner to align technical design with EP Wealth’s business strategy and compliance standards.

• Implement data validation, monitoring, and auditing to ensure data accuracy, completeness, and reliability.

• Collaborate with IT leadership to define and operationalize data governance standards.

• Troubleshoot and resolve data pipeline issues while maintaining system performance and uptime.

• Conduct query and warehouse optimization to ensure efficient Snowflake usage.

• Work closely with data analysts and technology teams to deliver accessible, well-documented data sets.

• Participate in design reviews, sprint planning, and architectural discussions with the implementation partner.

• Identify opportunities to extend Snowflake functionality through features such as Snowpark, data sharing, or automation tools.

• Stay informed on Snowflake’s evolving ecosystem and cloud data engineering best practices.

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