Engineer II, Data (Cloud & AI)

lplfinancial; Fort Mill (SC); On-site; USD 110,000 - 160,000; 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. This role blends AWS cloud engineering, data pipeline development, platform reliability, and AI-assisted software development to accelerate engineering outcomes while supporting mission-critical production systems.

The ideal candidate combines strong data engineering fundamentals with AWS experience and practical AI tool usage to improve productivity,

Qualifications

• Bachelor's or Master's degree in CS/Engineering or related field with relevant data/cloud engineering experience.
• Hands-on AWS experience with S3, Lambda, Glue, CloudWatch, IAM, EventBridge, and Athena.
• Proficiency in Python and PySpark for data transformation, SQL, API integrations, and Git/GitHub.

Responsibilities

• Design, develop, and maintain cloud-based data ingestion and transformation pipelines.
• Support onboarding of new vendor and enterprise data sources.
• Build infrastructure using Terraform and CI/CD pipelines.
• Develop automated data quality validation processes.
• Improve platform observability, reliability, and disaster recovery readiness.
• Collaborate with product managers, architects, analysts, and data consumers.

Skills

AWS

Python

PySpark

SQL

API Integrations

Git/GitHub

Data Pipelines

Automation

Education

Bachelor's degree in Computer Science, Engineering, or related field

Master's degree in CS/AI/Data Engineering or related field

Tools

Terraform

Lambda

Glue

S3

Athena

CloudWatch

IAM

EventBridge

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:

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 prac