About the job
You will be part of an Engineering team that builds and operates scalable, intelligent data platforms enabling analytics, automation and AI-driven decision-making across the organization for Fintech space. Our work focuses on designing high-performance data systems, ensuring reliability and operational excellence and integrating Generative AI capabilities to enhance how data is processed, understood and used. We work at the intersection of data engineering and applied AI, developing production-grade agentic systems that handle data at scale, automate complex workflows, and drive measurable business impact
Responsibilities
Architect Data & application Systems at Scale: Design large-scale, distributed data architectures capable of processing massive datasets, integrating AI-driven workflows, and supporting real-time and batch processing needs.
Drive System Design and Execution: Architect, develop, and deploy application and data processing engine — enabling autonomous orchestration of data pipelines, analytics, and business workflows.
Lead End-to-End Productionization : Own the full lifecycle — build, containerize, deploy, and maintain apps across environments using Kubernetes, Terraform, and CI/CD systems, spark.
Define and Enforce Engineering Standards: Set best practices around code quality, observability, scalability, and operational readiness for AI and data systems.
Guide Data and Infrastructure Decisions: Lead design discussions for data modeling, system integrations, and infrastructure architecture on Google Cloud Platform (GCP) and related technologies.
Enable Observability, Traceability & Reliability: Establish end-to-end monitoring and observability frameworks (e.g., Prometheus, Grafana, OpenTelemetry) for data services, ensuring deep traceability of agentic interactions.
Collaborate Across Teams and Domains:Partner with Product, Data Science teams to align Gen AI initiatives with data engineering objectives — ensuring production reliability and scalability.
Mentor and Grow Engineers: Provide technical mentorship to senior and mid-level engineers, fostering a culture of innovation, ownership, and operational excellence.
Champion Operational Efficiency: Identify and automate pain points in deployment, scaling, and monitoring. Drive continuous improvement in system reliability, performance, and developer productivity.
Own System-Level Decision Making: Evaluate new technologies, frameworks, and design patterns across LLMs and data infrastructure to guide the organization’s technical direction.
Qualifications
Minimum
Option 1: Bachelor's degree in computer science, computer engineering, computer information systems, software engineering, or related area and 3 years’ experience in software engineering or related area.
Option 2: 5 years’ experience in software engineering or related area.
Preferred
Master’s degree in computer science, information technology, engineering, information systems, cybersecurity, or related area and 1 year’s experience leading information security or cybersecurity projects, We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart’s accessibility standards and guidelines for supporting an inclusive culture.