Cloud & AI Data Engineer II — AWS Pipelines

lplfinancial

Fort Mill (SC)

On-site

USD 110,000 - 160,000

Full time

3 days ago
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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

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,

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