Senior AVP - Data Platform Backend Engineer (Python/AWS)

LPL Financial; New York (NY); Hybrid; USD 127,000 - 212,000; Full time

Benefits offered by this job

401K matching

Health benefits

Employee stock options

Paid time off

Job summary

LPL Financial is seeking an AVP Software Engineer in Data Technology to design and build scalable Python-based backend services for enterprise data pipelines in a hybrid role. You will work on data ingestion, transformation, and distribution within the Connectics team on a modern data platform.

The ideal candidate has strong Python skills, AWS serverless experience, and familiarity with data platforms and UI in React. Collaboration with Data and Analytics teams is essential.

Qualifications

• 7+ years of software engineering with Python backend experience.
• 5+ years building scalable backend services, REST APIs, and distributed systems.
• 5+ years developing cloud-native apps on AWS with production workloads.

Responsibilities

• Design, develop, and maintain scalable Python backend services for data integration and distribution.
• Build data pipeline frameworks for batch ingestion, transformation, and orchestration.
• Develop cloud-native apps using AWS serverless tech (Lambda, DynamoDB, API Gateway, EventBridge, SQS, Step Functions).
• Improve observability, monitoring, and resilience across pipelines and services.
• Collaborate with Data, AI, and Analytics teams to expose data and metrics for ML use cases.

Skills

Python backend

AWS

React

Data pipelines

Databricks

CI/CD

REST APIs

Observability

Education

Bachelor's degree in Computer Science or Engineering

Tools

Snowflake

Airflow

DATASCIENCE & ML tooling

Job description

LPL Financial is seeking an AVP Software Engineer in Data Technology to design and build scalable Python-based backend services for enterprise data pipelines in a hybrid role. You will work on data ingestion, transformation, and distribution within the Connectics team on a modern data platform.

The ideal candidate has strong Python skills, AWS serverless experience, and familiarity with data platforms and UI in React. Collaboration with Data and Analytics teams is essential.