Engineer II, Data (Cloud & AI)

LPL Financial; Fort Mill (SC); On-site; USD 114,903,000 - 191,495,000; Full time

Job summary

LPL Financial is seeking an Engineer II, Data (Cloud & AI) to design, build, and operate cloud-native data solutions at enterprise scale. You will work across data ingestion, transformation, and validation pipelines on AWS, using Terraform IaC, and apply AI-assisted development tools to boost velocity while maintaining production reliability.

The role emphasizes scalable data pipelines, platform observability, and collaboration with product managers and engineers to improve data governance and

Qualifications

• Bachelor’s degree in Computer Science, Engineering or related field; 3+ years of software/cloud/data engineering OR Master’s with 1+ year relevant experience.
• Experience building, supporting, or maintaining cloud-based applications, data platforms, or production systems.
• Hands-on experience with AWS services including S3, Lambda, Glue, CloudWatch, IAM, EventBridge, and Athena
• Proficiency in Python and/or PySpark for data transformation, SQL, API integrations, and Git/GitHub
• Experience in ETL/ELT pipelines, data validation, data quality practices, and batch/event-driven processing

Responsibilities

• Design, develop, and maintain cloud-based data ingestion and transformation pipelines.
• Onboard new vendor and enterprise data sources.
• Optimize processing performance for large data volumes.
• Build reusable ingestion, validation, and transformation frameworks.
• Develop automated data quality validation processes.
• Develop AWS-based solutions and Terraform infrastructure.
• Support CI/CD deployment pipelines and observability.
• Explore AI-assisted development tools to improve velocity and efficiency.
• Participate in incident response and production support.
• Collaborate with product managers, architects, analysts, and business stakeholders.

Skills

Python

PySpark

SQL

Git/GitHub

Data engineering

Education

Bachelor's degree in CS/Engineering

Master's degree in CS/Data AI/IS

Tools

AWS services

Terraform

CI/CD pipelines

OpenAI APIs

Bedrock

Vector databases

Job description

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:

LPL Financial is looking for an Engineer II, Data who can build and operate cloud-native data solutions at enterprise scale. This role combines AWS cloud engineering, data pipeline development, platform reliability, and AI-assisted software development. The ideal candidate enjoys solving operational challenges, automating manual processes, and using modern AI tools to accelerate engineering outcomes while supporting mission-critical production systems.

The Engineer II, Data (Cloud & AI) is responsible for designing, building, supporting, and optimizing cloud-native data solutions within the Enterprise Data Integration Framework (EDIF).

This role supports the ingestion, validation, transformation, enrichment, and standardization of enterprise data while leveraging modern cloud and AI technologies to improve engineering productivity, operational efficiency, and platform observability.

The ideal candidate combines strong data engineering fundamentals with AWS cloud experience and practical experience using AI-assisted development tools and generative AI technologies.

Job Responsibilities

Data Engineering

• Design, develop, and maintain cloud-based data ingestion and transformation pipelines.
• Support onboarding of new vendor and enterprise data sources.
• Optimize processing performance for large-volume datasets.
• Build reusable ingestion, validation, and transformation frameworks.
• Develop automated data quality validation processes.

Cloud Engineering

• Develop and support AWS-based solutions.
• Build infrastructure using Terraform and Infrastructure as Code practices.
• Support CI/CD deployment pipelines.
• Improve platform scalability, resiliency, and disaster recovery readiness.
• Implement monitoring and observability capabilities.

AI-Assisted Engineering

• Utilize AI coding assistants to improve development velocity and engineering efficiency.
• Develop proof-of-concept solutions leveraging LLMs and generative AI services.
• Build intelligent operational tooling for monitoring, troubleshooting, and support workflows.
• Identify opportunities where AI can reduce engineering effort or improve service delivery.
• Evaluate and implement AI-driven automation capabilities within established governance standards.

Production Support & Reliability

• Participate in application support and incident response processes.
• Troubleshoot and resolve production pipeline failures.
• Conduct root cause analysis and drive preventative improvements.
• Support platform monitoring and operational reporting.Contribute to runbooks and operational documentation.

Collaboration

• Participate in Agile ceremonies and sprint activities.
• Work closely with product managers, architects, analysts, and business stakeholders.
• Collaborate with vendor teams and upstream/downstream data consumers.
• Contribute to architecture discussions and technical design reviews.

Key Objectives

• Deliver scalable and resilient data ingestion solutions.
• Improve AWS cloud infrastructure and operational maturity.
• Implement AI-enabled engineering solutions where appropriate.
• Reduce manual support effort through automation.
• Maintain high platform availability and service quality.
• Support enterprise data governance and security standards

What Are We Looking For?

We are seeking motivated engineers who thrive in a fast-paced, cloud-first data environment and are eager to work at the intersection of data engineering and AI-augmented development. An ideal candidate demonstrates:

• Build scalable cloud data pipelines.
• Improve platform reliability and operational excellence.
• Automate manual engineering processes.
• Leverage AI technologies to accelerate delivery.
• Reduce operational overhead through intelligent tooling.
• Support modernization initiatives across cloud and data platforms.

Requirements

• Bachelor’s degree in Computer Science, Engineering or related field with minimum of 3 years of experience in software engineering, cloud engineering, platform engineering, or data engineering OR Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, Information Systems, Engineering, or a related field with minimum of 1 year of relevant experience.
• Demonstrated experience building, supporting, or maintaining cloud-based applications, data platforms, or production systems.
• Hands-on experience with AWS services including S3, Lambda, Glue, CloudWatch, IAM, EventBridge, and Athena
• Proficiency in Python and or PySpark for data transformation, SQL, API Integrations, and Git/GitHub
• Experience in data engineering to include, ETL/ELT pipeline development, Data validation frameworks, Data quality practices, and Batch and event-driven processing

Core Competencies

• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent debugging and troubleshooting capabilities
• Effective communication and collaboration
• Ability to work independently and deliver in fast-paced environments
• High attention to detail and commitment to data quality
• Ability to work independently while collaborating effectively within Agile teams.
• Continuous learning mindset, including adoption of AI-assisted engineering practices in a responsible manner

Preferences

• AWS certification(s).
• Financial services experience.
• Data platform engineering.
• Event-driven architectures.
• Large-scale file processing.
• Production support and on‑call responsibilities.
• Observability and monitoring platforms.
• Terraform, Infrastrucutre as Code, CI/CD pipelines
• Experience building solutions using:
• Amazon Bedrock
• Azure OpenAI
• OpenAI APIs
• Vector databases
• Retrieval Augmented Generation (RAG)
• Understanding of:
• Prompt engineering
• LLM evaluation
• AI governance and security
• Agentic workflows
• AI-powered automation

Pay Range:

$40.10-$66.83/hour

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. 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 [phone].

EAC 5.19.26