Senior Data Engineer

About the role

This role centers on expanding a centralized data ecosystem, moving beyond initial data ingestion to integrate various financial and operational data streams. The primary objective is to create a reliable reporting layer that supports strategic decisions for C-level executives and advisors. The work involves building and maintaining scalable data pipelines, developing data transformations, and orchestrating complex workflows.

A key part of the work includes designing specialized data models for portfolio, client, and financial reporting. The engineer will also ensure data quality, lineage, and governance while optimizing performance and cost within Snowflake. This position requires collaboration with Tableau developers and business stakeholders to ensure technical solutions meet reporting requirements.

Success in this position means delivering a robust and scalable data infrastructure that provides accurate and timely financial insights. It requires a focus on integrating diverse data sources and transforming them into a unified, reliable format. The ideal candidate will contribute to a high-growth phase, enhancing the company's ability to leverage data for strategic advantage.

The listed salary range for this role is $42,000 to $70,000 USD annually.

Skills that matter here

• Snowflake: This role requires building and maintaining scalable data pipelines for ingestion into Snowflake, and optimizing performance and costs within it.
• dbt: The engineer will develop and manage data transformations using dbt, including modeling, testing, and documentation.
• SQL: Strong SQL skills are essential for data modeling and managing data within the ecosystem.
• Prefect: This position involves designing and orchestrating complex data workflows using Prefect.
• Python: Python is part of the technology stack, indicating its use in data engineering tasks.
• Tableau: The engineer will partner with Tableau developers to align technical delivery with reporting needs.

Who this role suits

• A data engineer with at least five years of experience focused on modern data platform construction.
• Someone who possesses a DBT certification and advanced data modeling expertise.
• An individual with practical experience in ETL/ELT patterns and API-based ingestion.
• A professional familiar with financial or wealth management data structures.

From the employer

• Build and maintain scalable data pipelines for ingestion into Snowflake.
• Develop and manage transformations using dbt, including modeling, testing, and comprehensive documentation.
• Design and orchestrate complex data workflows using Prefect.
• Utilize Workato to integrate and normalize data from critical SaaS platforms, including Addepar, NetSuite, Salesforce, Morningstar, and UKG.
• Design specialized data models tailored for portfolio, client, and financial reporting.
• Ensure data quality, lineage, and governance best practices while optimizing performance and costs within Snowflake.
• Partner with Tableau developers and business stakeholders to align technical delivery with reporting needs.

• 5+ years of experience in data engineering with a focus on building modern data platforms.
• Hands-on experience with Snowflake and dbt, supported by strong SQL skills and advanced data modeling expertise.
• DBT certification.
• Proven familiarity with ETL/ELT patterns and API-based ingestion.
• Practical experience with orchestration tools such as Prefect or Airflow.
• A solid understanding of financial or wealth management data structures.