Staff/Principal Software Engineer (Data Pipelines)

At Advisor360°, we build technology that transforms how wealth management firms operate, scale, and serve their clients. As a leading SaaS platform in the fintech space, we’re trusted by some of the largest independent broker-dealers and RIAs to power the full advisor and client experience—from portfolio construction and reporting to compliance and client engagement. 

What sets us apart? It's not just the tech (though it's best-in-class). It's the people, the purpose, and the passion behind everything we do. 

We’re a team of builders, thinkers, and doers who believe that great companies are defined by the stories they tell and the experiences they create—internally and externally. We bring deep industry expertise, a collaborative spirit, and a commitment to innovation as we reshape what’s possible in wealth management. 

As we grow, we’re looking for teammates who are ready to roll up their sleeves, think big, and help elevate our brand in a way that reflects the bold ambitions we have for our company and the clients we serve. Join us, and be part of a company that's not only moving fast—but making it count. 

This role is hybrid, requiring three days per week onsite in our Needham, MA headquarters.  

Key Responsibilities:

• Acts as a technical leader (at a Sr. Manager/Director level, but it is an IC role) by making significant technical contributions to the planning and implementation of mid to large-scale projects from conception to completion. This role is less than 50% coding. It is planning, designing, firefighting - working across the org.

• Soft skills are as important as tech skills. Breadth is important. Experience in data pipelines is key as well as experience with Snowflake.

• Demonstrates versatility of knowledge and applies strong technical skill sets to architect and implement cloud-based data solutions. 

• Validates requirements, performs business and technical analysis, designs cloud-native applications, writes optimized PySpark-based data pipelines, and contributes to end-to-end application development. 

• Ensures compliance with coding standards and best practices for AI-assisted code generation, suggesting opportunities for improvement. 

• Utilizes GenAI tools like Cursor, Claude, and other LLMs to decompose complex requirements and auto-generate UI, API, and database scripts for rapid development. 

• Acquires and utilizes strong technical and application knowledge to introduce and forecast the impact of new software design patterns, AI-driven development workflows, and emerging cloud technologies. 

• Partners with stakeholders and product managers in an agile environment to refine evolving product requirements, rapidly prototype solutions, and deliver technically sound features aligned with market needs and business goals. 

• Shares information and expertise to improve team productivity and empower engineers with AI-driven automation. 

• Acts as a subject matter expert (SME) within the organization, helping resolve complex technical issues related to cloud data engineering, distributed computing, and microservices architecture. 

• Mentors team members and fosters collaborative learning environments, particularly in areas related to GenAI, Azure, PySpark, Databricks, Snowflake and CI/CD automation. 

• Leads multiple projects within the team, ensuring seamless integration of AI-driven development into software delivery pipelines. 

Requirements, Skills, and Knowledge:

• 10+ years of software engineering experience building enterprise applications using Python, .NET. 

• Proven ability to analyze, decompose, and automate requirement-based development using GenAI. 

• Strong experience in building and deploying cloud-based data processing applications using PySpark and Azure Databricks. 

• Hands-on expertise in automating and optimizing cloud native, container applications.

• Experience implementing business-critical database applications, REST microservices, and real-time event-driven architectures using Kafka, Orkes, and Databricks. 

• Deep knowledge of SDLC methodologies (Agile, DevOps) and experience leading technical implementations from architecture to production deployment. 

• Proficiency in coding standards, code reviews, source control management, build processe