Overview

Our team designs data and semantic models that empower HR, business, and analytics teams to make data-driven decisions at scale.

Responsibilities

• Own the architecture, design, and delivery of scalable batch and future streaming data pipelines using Spark, Big Query, Airflow, and related cloud-native technologies.
• Drive best practices across data modeling, pipeline reliability, observability, and cost optimization to ensure high performance and availability.
• Define and implement the data security framework for the lake, including encryption (at rest and in transit), masking and fine-grained access controls.
• Establish secure data sharing and governance mechanisms to protect sensitive data and ensure regulatory and enterprise compliance.
• Partner with Product, HR, Analytics, Security, and Architecture teams to define roadmap, prioritize initiatives, and deliver scalable, resilient, and secure data solutions.
• Build a strong engineering culture focused on operational excellence, technical rigor, and continuous improvement while shaping the mid- to long-term platform vision.
• Establish best engineering and operational excellence practices based on product, engineering, and scrum metrics.
• Work with senior leadership to chart out the future roadmap of the products
• Participate in hiring, mentoring, and building high performing agile teams.
• Establishing clear expectations with individuals based on their level and role, meeting regularly to discuss performance, provide feedback and coaching

Qualifications

• 12+ years of experience in software or data engineering with 3+ years leading high-performing engineering teams.
• Strong hands-on expertise in Spark, BigQuery, Airflow (or equivalent), and distributed data systems on GCP.
• Proven experience designing, building, and operating large-scale data lakes or lakehouse platforms with batch and streaming ingestion.
• Deep understanding of data security principles including encryption, PII protection, masking, IAM, and row/column-level security.
• Strong SQL and data modeling skills with experience implementing CI/CD, monitoring, and reliability best practices for data platforms.
• Ability to operate at both strategic and execution levels, influence cross-functional stakeholders, and translate platform vision into secure, scalable business outcomes.
• Knowledge in Pub sub system like Kafka.
• Knowledge of cloud platforms like Azure, GCP etc
• Lead the integration of AI/ML toolkits and frameworks into day-to-day (D2D) data engineering workflows, enabling teams to accelerate development, automate data processes, and enhance decision-making capabilities.

Nice to have

• Primary Location...Tower 1, Part Of 1st, 2nd To 4th Flrs, Intl Tech Park Radial Road (radial It Park Pvt Ltd), , India

Benefits

• Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include a host of best-in-class benefits maternity and parental leave, PTO, health benefits, and much more.
• We aim to create a culture where every associate feels valued for who they are, rooted in respect for the individual. Our goal is to foster a sense of belonging, to create opportunities for all our associates, customers and suppliers, and to be a Walmart for everyone.
• At Walmart, our vision is everyone included. By fostering a workplace culture where everyone isand feelsincluded, everyone wins. Our associates and customers reflect the makeup of all 19 countries where we operate. By making Walmart a welcoming place where all people feel like they belong, were able to engage associates, strengthen our business, improve our ability to serve customers, and support the communities where we operate.
• Equal Opportunity Employer:
• Walmart, Inc. is an Equal Opportunity Employer By Choice. We believe we are best equipped to help our associates, customers and the communities we serve live better when we really know them. That means understanding, respecting, and valuing unique styles, experiences, identities, ideas and opinions while being welcoming of all people.