Senior Data Engineer

Client

Our client is a prominent global wealth and asset management firm focused on delivering innovative investment solutions and a networked ecosystem of international opportunities. The organization operates within a highly regulated environment, prioritizing the transformation of complex concepts into actionable financial strategies for a global clientele.

Project overview

The project involves the development and expansion of a centralized, scalable data ecosystem. Having successfully ingested the initial data source, the team is now moving into a high-growth phase to integrate multiple high-value financial and operational data streams. The goal is to provide C-level executives and advisors with a unified, reliable reporting layer for strategic decision-making.

Position overview

As a Senior Data Engineer, you will be a technical cornerstone of the data platform team. You will be responsible for the end-to-end engineering of data pipelines, from ingestion to transformation, ensuring that the Snowflake warehouse is optimized for complex wealth management analytics. You will work at the intersection of sophisticated financial data and enterprise-grade engineering.

Responsibilities

• Design, build, and maintain scalable automated ETL/ELT pipelines to ingest data from diverse sources including Addepar, NetSuite, Salesforce, Morningstar, Bloomberg, and UKG.
• Architect and implement robust data models within Snowflake using DBT (Data Build Tool) to ensure high-performance transformations and clean data structures.
• Utilize Workato to orchestrate seamless integrations between third-party SaaS platforms and the central data warehouse.
• Monitor and optimize Snowflake performance, storage, and compute usage to ensure cost-effectiveness and reliability.
• Partner with Business Analysts and Tableau Engineers to ensure the data layer effectively supports complex business use cases and executive dashboards.
• Implement rigorous data validation and testing frameworks to maintain high data integrity, especially critical given the regulated nature of investment data.

Requirements

• Extensive hands-on experience as a Data Engineer focusing on Snowflake architecture, including advanced performance tuning and security features.
• Proven proficiency with DBT for data transformation and Workato (or similar enterprise integration platforms) for workflow automation.
• Strong ability to understand complex financial datasets and translate business-centric data needs into technical schemas.
• Solid understanding of software engineering best practices, including version control (Git) and CI/CD pipelines for data.
• Exceptional ability to communicate technical concepts effectively with both business stakeholders and cross-functional technical teams.

Nice to have

• Experience supporting reporting requirements for Tableau-based visualization layers.
• Experience within the Wealth Management or Investment Management sector, with specific familiarity handling investment and portfolio-related data.
• Understanding of regulatory requirements regarding financial data handling and privacy.
• Background in integrating market data providers such as Bloomberg or Morningstar.
• Advanced SQL skills and experience with Python for data engineering tasks.