AVP, Software Engineering Data Engineer with Python and AWS

LPL Financial · Banking & Financial Services

Hyderabad
On-site
Posted yesterday
Apply by 25 Oct
Software Engineering

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About the job

Where Ambition Meets Innovation

At LPL’s Global Capability Center , you'll find a collaborative culture where your voice matters, integrity guides every decision, and technology fuels progress. Your skills, talents, and ideas will redefine what's possible. LPL's success reflects its exceptional employees, who together pursue one noble purpose: empowering financial advisors to deliver personalized advice for all who need it. We’re proud to be expanding and reaching new heights in Hyderabad.

Join us as we create something extraordinary together.

AVP, Software Engineering — Direct Business & LDX | LPL Technologies

At LPL Financial Global Capability Center, you'll find a collaborative culture where your voice matters, integrity guides every decision, and technology fuels progress. Your skills, talents, and ideas will redefine what's possible. LPL's success reflects its exceptional employees, who together pursue one noble purpose: empowering financial advisors to deliver personalized advice for all who need it. We are proud to expand in Hyderabad.

Join us as we create something extraordinary together.

Job Overview:

We are seeking a highly skilled AVP to join our Direct Business and LPL Data Experience (LDX) team . This role is critical to designing and implementing modern, cloud‑based data and application capabilities that will transform how Direct business data is ingested, managed and leveraged for various business functionalities within the firm for advisors, investors cross the enterprise. This role is critical to designing and implementing modern, cloud‑based data and application capabilities that will transform how compensation processing, data flows, validation, and automation operate across the enterprise.

This is a data engineering–leaning leadership role: you will guide teams building pipelines, APIS, integrations, and data services alongside the applications that consume them. The ideal candidate combines strong data engineering fundamentals with hands-on credibility in Python, AWS, and SQL/relational data platforms , and can drive modernization without destabilizing production.

You will work closely with architects, product teams, compensation SMEs, and engineering partners to deliver scalable, resilient, and future‑ready systems that modernize the compensation platform end‑to‑end.

Responsibilities:

Leadership : Build, coach, and develop engineers; set a culture of ownership, craftsmanship, and customer empathy. Hire and grow leaders.

Modernization : Drive a pragmatic roadmap to improve architecture, reduce risk, retire debt, and migrate toward durable cloud patterns—without “big bang” disruption to the business.

Quality at scale : Establish engineering standards for reliability, security, observability, testing, and operational readiness in business-critical systems.

Cross-functional partnership : Work tightly with Product, Architecture, Platform, Security, Operations, and business stakeholders to prioritize outcomes, manage trade-offs, and communicate clearly upward and outward.

AI, two ways: For customers and operations: identify high-value workflows (onboarding, exceptions, validations, investigations, decision support) where intelligent automation improves speed, accuracy, and auditability—within LPL governance. For engineering: accelerate delivery responsibly (design assistance, code/test/docs workflows) with standards that protect quality, security, and compliance.

What you will bring (hands-on to lead credibly) You are expected to be technically credible with complex enterprise systems—even as your primary job is leading the team. You should be comfortable diving into architecture reviews, critical incidents, and the hardest design decisions.

What are we looking for?

We’re looking for strong collaborators who deliver exceptional client experiences and thrive in fast-paced, team-oriented environments. Our ideal candidates pursue greatness , act with integrity , and are driven to help our clients succeed . We value those who embrace creativity, continuous improvement, and contribute to a culture where we win together and create and share joy in our work.

Requirements:

12+ years software engineering experience in enterprise environments; 5+ years leading engineering teams (managers and senior ICs).

Track record shipping and operating mission-critical applications; experience in regulated / financial services strongly preferred.

Demonstrated data engineering experience: designing and operating batch and/or event-driven pipelines , integrations, and data services for mission-critical workflows.

Strong SQL and RDBMS skills: data modelling, query optimization, performance tuning, and data quality/validation practices.

Demonstrated success leading modernization programs (incremental migration, platform patterns, service boundaries, strangler approaches) while keeping production stable. ave ability to introduce AI-enabled capabilities and/or AI-accelerated engineering with measurable impact and appropriate controls.

Hands-on Python development (e.g. FastAPI, Flask, or Django ) for services and data-oriented workloads.·

Cloud-native delivery on AWS (e.g. S3, Lambda, RDS, EKS ) with attention to scalability, security, and operations.

How you work Systems thinking, decisive prioritization, calm under ambiguity, and executive-ready communication. You raise the bar by clarifying standards, not by adding process for its own sake.

Core Competencies:

A healthier technical foundation: clearer ownership, better observability, fewer repeat incidents, faster safe releases.

A team that attracts and retains strong engineers—and ships modernization milestones on a credible cadence.

A small set of high-confidence AI wins (operations and/or product) with documented guardrails and measurable outcomes.

Preferences:

Domain familiarity with advisor/practice onboarding, compensation, registration/licensing workflows, or fee/billing platforms.

Experience with distributed systems, APIs, event-driven patterns, and pragmatic microservices where they earn their complexity.

Background shaping CI/CD, automated testing strategy, SRE practices, incident learning, and engineering metrics.

Familiarity with model/workflow governance, monitoring, and responsible AI practices in enterprise settings.

Angular/React and . NET/C# APIs where they support data and application surfaces.

AWS OpenSearch or similar enterprise search/indexing.

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