AVP, Data Reliability Tech Lead

LPL Financial•Charlotte, NC

About The Position

As the AVP, Data Reliability Tech Lead , you will lead the modernization, and operation of reliable, fault-tolerant, and observable data systems across LPL’s enterprise data platform. You’ll guide a team of engineers focused on ensuring that data is accurate, available, and auditable , while supporting the transformation of legacy SSIS and on-prem systems into modern, AWS and Snowflake-based architectures . This is a hands-on technical leadership role that combines deep engineering expertise with strategic vision.

Requirements

7+ years in data engineering, reliability, or platform development roles.
2+ years leading technical teams or projects.
2+ years of experience with AWS services (e.g., Glue, Lambda, S3) and Snowflake .
Strong proficiency in SSIS and SQL Server for ETL and data integration.
Skilled in Python and SQL for pipeline development and automation.
Strategic thinker with a focus on data reliability, automation, and scalability .
Proven ability to lead and mentor engineering teams .
Strong communication and stakeholder management skills.
Demonstrated success in delivering fault-tolerant, observable, and modernized data systems .

Nice To Haves

Financial services or regulated industry experience (FINRA/SEC familiarity).
Exposure to streaming architectures (Kafka, Kinesis) and near real-time data delivery.
Certifications in AWS , Snowflake , or related data engineering disciplines.
Strong understanding of data quality , lineage , and metadata management principles.

Responsibilities

Data Reliability and Observability Support the reliability of data pipelines and platforms across AWS , Snowflake , and SSIS .
Develop and implement observability frameworks using tools such as Dynatrace for proactive monitoring, alerting, and performance analytics.
Maintain data SLAs , support anomaly detection, and reconciliation processes.
Leverage and help update systems that prevent and rapidly detect data degradation, latency, or loss events.
Lead incident response, root cause analysis, and continuous improvement initiatives for data reliability.
Modernization Leadership Support the modernization of legacy SSIS and SQL Server ETL systems into cloud-native, event-driven data pipelines using modern data architectures.
Champion data best practices: CI/CD pipelines, automated testing, and infrastructure as code (Terraform).
Collaborate with architects to standardize resilient, scalable patterns for ingestion, transformation, and distribution.
Promote automation and self-healing across the data ecosystem to improve reliability and reduce manual intervention.
Technical Leadership and Collaboration Lead and mentor a team of data engineers focused on reliability, observability, and modernization.
Partner with Data Governance , Risk , and Compliance to align data reliability with enterprise controls and regulatory requirements.
Contribute to strategic roadmaps, capacity planning, and reliability-focused design reviews.
Advocate for a culture of reliability engineering and continuous improvement across the data organization.