Sr Engineer

LPL Financial Global Capability Center; Hyderabad; On-site; INR 4,500,000 - 6,000,000; Full time

Job summary

LPL Global Capability Center in Hyderabad is seeking a Senior AWS Data Engineer with 8+ years of experience to build scalable, secure data platforms and enable data-driven decision-making across the enterprise.

You will design, develop, and operate data pipelines using AWS, Python, Spark, and APIs, collaborating with platform, architecture, and DevOps teams to ensure reliability and governance.

Qualifications

• BS in Computer Science, Engineering, or equivalent practical experience.
• 8+ years of experience in data engineering or distributed systems development.
• Strong hands‑on experience with AWS cloud services.
• Advanced proficiency in Python.
• Hands‑on experience with Apache Spark.
• Experience building event‑driven data pipelines.
• Experience designing distributed data processing architectures.
• Strong knowledge of data quality, data lineage, and orchestration.
• Experience in API development.
• Hands‑on experience with Docker and Kubernetes.

Responsibilities

• Data Pipeline Development: Design, develop, and maintain distributed data pipelines on AWS that ingest, process, and deliver data at scale. Implement both batch and event-driven data processing patterns using AWS-native services.
• Event-Driven Architecture: Build and support event-driven data solutions using asynchronous, decoupled architectures to enable near real-time processing and system scalability.
• Technical Expertise: Provide hands‑on engineering using Python and Apache Spark to process large datasets efficiently. Apply best practices in distributed systems, performance optimization, and fault tolerance.
• Data Quality, Lineage & Orchestration: Ensure end-to-end data quality, implement validation and monitoring checks, establish data lineage, and manage orchestration workflows to ensure reliable and auditable data movement.
• API Development: Design and develop RESTful and event-driven APIs to expose data and data services to internal and external consumers.
• Containers & Cloud-Native Development: Build and deploy data services using Docker containers and manage workloads on Kubernetes following cloud‑native and DevOps best practices.
• Stakeholder Collaboration: Collaborate with data consumers, architects, platform teams, and business stakeholders to gather requirements, design scalable solutions, and deliver high-quality outcomes.
• Operational Excellence: Contribute to monitoring, logging, alerting, and incident response for data platforms. Ensure systems meet reliability, performance, and security standards.

Skills

Python

Apache Spark

AWS cloud services

Education

BS in Computer Science, Engineering, or equivalent practical experience

Tools

Docker

Kubernetes

Job description

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.

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.

Job Overview

We are seeking an accomplished Senior Data Engineer with 8+ years of experience who will be part of the Data & Platform Engineering organization responsible for building scalable, secure, and high-performance data platforms that support analytics, reporting, and downstream applications. This role is critical to enabling data-driven decision-making across the enterprise.

The Senior AWS Data Engineer requires strong hands-on cloud data engineering expertise, deep knowledge of distributed and event-driven architectures, and the ability to collaborate closely with application engineers, architects, and business stakeholders. This role plays a key part in designing, developing, and operating data pipelines that meet high standards for reliability, data quality, lineage, and governance.

The Senior AWS Data Engineer will contribute to building modern, cloud-native data solutions leveraging AWS, Python, Spark, APIs, and containers. They will also partner with platform, architecture, and DevOps teams to ensure consistency, scalability, and operational excellence across data pipelines.

Responsibilities

Data Pipeline Development:

Design, develop, and maintain distributed data pipelines on AWS that ingest, process, and deliver data at scale. Implement both batch and event-driven data processing patterns using AWS-native services.

Event-Driven Architecture:

Build and support event-driven data solutions using asynchronous, decoupled architectures to enable near real-time processing and system scalability.

Technical Expertise:

Provide hands‑on engineering using Python and Apache Spark to process large datasets efficiently. Apply best practices in distributed systems, performance optimization, and fault tolerance.

Data Quality, Lineage & Orchestration:

Ensure end-to-end data quality, implement validation and monitoring checks, establish data lineage, and manage orchestration workflows to ensure reliable and auditable data movement.

API Development:

Design and develop RESTful and event-driven APIs to expose data and data services to internal and external consumers.

Containers & Cloud-Native Development:

Build and deploy data services using Docker containers and manage workloads on Kubernetes following cloud‑native and DevOps best practices.

Stakeholder Collaboration:

Collaborate with data consumers, architects, platform teams, and business stakeholders to gather requirements, design scalable solutions, and deliver high-quality outcomes.

Operational Excellence:

Contribute to monitoring, logging, alerting, and incident response for data platforms. Ensure systems meet reliability, performance, and security standards.

What are we looking for?

We are looking for strong data engineers who can deliver reliable, scalable, and high‑quality data solutions. The ideal candidate thrives in a fast‑paced environment, is passionate about data engineering, and is comfortable working across teams to solve complex data problems.

Requirements

• BS in Computer Science, Engineering, or equivalent practical experience
• 8+ years of experience in data engineering or distributed systems development
• Strong hands‑on experience with AWS cloud services
• Advanced proficiency in Python
• Hands‑on experience with Apache Spark
• Experience building event‑driven data pipelines
• Experience designing distributed data processing architectures
• Strong knowledge of data quality, data lineage, and orchestration
• Experience in API development
• Hands‑on experience with Docker and Kubernetes

Preferences

• Experience with CI/CD pipelines and DevOps practices.
• Familiarity with backend services, microservices, or serverless architectures on AWS.
• Experience working in Agile delivery teams.
• Knowledge of observability, monitoring, and production support practices.

Core Competencies

• Excellent verbal and written communication skills
• Strong analytical and problem‑solving skills
• Ability to collaborate with cross‑functional teams
• Strong ownership mindset and attention to detail
• Experience working in Agile environments
• Commitment to continuous learning

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