AVP Software Engineer - Data Platform Engineering (Python/AWS)

Where Ambition Meets Innovation

Build a career that matches all your initiative with an impressive dose of innovation. From cutting-edge resources and a collaborative environment to the freedom to make an impact and more, you’ll find the ingredients you need at LPL Financial to shape your success while helping clients pursue their financial goals.

Job Overview:

This is a unique opportunity to help build and scale a strategic platform at the center of LPL's modern data ecosystem. The team is responsible for batch integration, data sourcing, data movement, and delivering trusted data products to downstream consumers across the enterprise.

As an AVP Software Engineer in Data Technology, you will play a key role in designing and developing highly scalable backend services, data processing capabilities, and monitoring solutions that support complex enterprise data pipelines. You will help build innovative capabilities to monitor, visualize, and analyze large-scale data flows while enabling intelligent detection of data quality issues, operational anomalies, and pipeline failures.

This role sits within the Connectics team, which is responsible for enterprise data integration, backend services, APIs, batch ingestion, and making trusted data assets available to downstream consumers across LPL's modern data platform. The primary focus is on building scalable Python-based services, integration frameworks, and cloud-native applications that enable data movement, access, and consumption across the organization.

The ideal candidate is a strong Python backend engineer with deep experience building data-intensive applications, cloud-native solutions, and modern data platform capabilities on AWS. While the role is primarily backend-focused, experience developing user interfaces with React is desirable.

Responsibilities:

• Design, develop, and maintain scalable Python-based backend services supporting enterprise data integration, enrichment, validation, and distribution.

• Build and enhance data pipeline frameworks supporting batch ingestion, transformation, orchestration, and downstream data consumption.

• Develop cloud-native applications leveraging AWS serverless technologies including Lambda, DynamoDB, API Gateway, EventBridge, SQS, and Step Functions.

• Develop reusable integration patterns that simplify connectivity between source systems, data platforms, and consuming applications.

• Improve observability, monitoring, and operational resilience across data pipelines and integration services.

• Leverage AI-assisted development tools and modern engineering practices to improve code quality, productivity, troubleshooting, and documentation.

• Collaborate with Data, AI, and Analytics teams to expose data and metrics that support machine learning and AI-driven use cases.

• Troubleshoot and resolve performance, scalability, and reliability challenges across distributed systems and large-scale data workloads.

• Work closely with stakeholders to understand their specific capabilities and needs and be able to think strategically on how to incorporate new capabilities into the system without creating one-off solutions.

• Be a team player, continue learning and help teach new or junior members of the team.

What are we looking for?

We want strong collaborators who can deliver a world-class client experience. We are looking for people who thrive in a fast-paced environment, are client-focused, team oriented, and are able to execute in a way that encourages creativity and continuous improvement.

Requirements:

• Minimum of 7 years of professional software engineering experience, including deep expertise in Python backend development and experience with React and modern JavaScript frameworks.

• Minimum of 5 years designing and building scalable backend services, REST APIs, and distributed systems in enterprise environments.

• Minimum of 5 years developing cloud-native applications on AWS, with hands-on experience building and supporting production workloads.

• Strong experience with AWS serverless technologies including Lambda, API Gateway, DynamoDB, EventBridge, SQS, and related services.

• Experience building modern data platform solutions, including batch processing, data integration, data ingestion, and enterprise data distribution pipelines.

Core Competencies:

• Strong Python engineering fundamentals, including application design, testing, performance tuning, and operational support.

• Working knowledge of React and modern JavaScript frameworks for developing operational dashboards and user interfaces.

• Experience building and integrating RESTful APIs and event-driven architectures.

• Experience with CI/CD pipelines, automated testing, DevOps practices, and cloud-native delivery models.

• Experience working within modern data platforms leveraging technologies such as Snowflake, Airflow, Databricks, or similar ecosystems.

• Understanding of data integration, data observability, monitoring, and operational resilience concepts.

• Understanding of how modern data platforms support analytics, machine learning, and AI-enabled workloads.

• Ability to operate effectively in ambiguous environments and solve complex technical challenges.

• Experience mentoring engineers, conducting code reviews, and contributing to engineering best practices.

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.

• This is a hybrid role, requiring onsite presence at an LPL Financial office 2–3 days per week, as much of the team and leadership are based there.

Pay Range: $127,100.00 - $211,900.00

Actual base salary varies based on factors, including but not limited to, relevant skill, prior experience, education, base salary of internal peers, demonstrated performance, and geographic location. Additionally, LPL Total Rewards package is highly competitive, designed to support your success at work, at home, and at play – such as 401K matching, health benefits, employee stock options, paid time off, volunteer time off, and more. Your recruiter will be happy to discuss all that LPL has to offer!

Company Overview:

LPL Financial Holdings Inc. (Nasdaq: LPLA) is among the fastest growing wealth management firms in the U.S. As a leader in the financial advisor-mediated marketplace(6), LPL supports over 32,000 financial advisors and the wealth management practices of approximately 1,100 financial institutions, servicing and custodying approximately $2.3 trillion in brokerage and advisory assets on behalf of approximately 8 million Americans. The firm provides a wide range of advisor affiliation models, investment solutions, fintech tools and practice management services, ensuring that advisors and institutions have the flexibility to choose the business model, services, and technology resources they need to run thriving businesses. For further information about LPL, please visit www.lpl.com.

At LPL, independence means that advisors and institution leaders have the freedom they deserve to choose the business model, services, and technology resources that allow them to run a thriving business. They have the flexibility to do business their way. And they have the freedom to manage their client relationships, because they know their clients best. Simply put, we take care of our advisors and institutions, so they can take care of their clients.

For further information about LPL, please visit www.lpl.com.

Join the LPL team and help us make a difference by turning life’s aspirations into financial realities. Please log in or create an account to apply to this position. Principals only. EOE.

Information on Interviews:

LPL will only communicate with a job applicant directly from an @lplfinancial.com email address and will never conduct an interview online or in a chatroom forum. During an interview, LPL will not request any form of payment from the applicant, or information regarding an applicant’s bank or credit card. Should you have any questions regarding the application process, please contact LPL’s Human Resources Solutions Center at (855) 575-6947.

EAC 5.19.26