- Location
- IN KA BANGALORE Home Office PTPP1, India
- Type
- Full-time
- Department
- Engineering
- Seniority
- Senior
- Experience
- 12+ years
- Education
- Master
- Source
- Workday
Description
Position Summary...
What you'll do...
About Team
GDF sits at the core of Walmart's AI & Data organization, building the foundational data platforms that make it possible for every team at Walmart — technical or non-technical — to build with trustworthy, well-governed, discoverable data. Our platforms serve billions of transactions and interactions across 19 countries, powering everything from supply chain intelligence to customer-facing personalization to enterprise AI agents. This particular team is newly formed to solve one of GDF's next big platform bets — which means you'll be shaping charter, operating model, and delivery cadence essentially from a blank page, not inheriting someone else's playbook.
What You'll Do
- Lead the engineering team(s) responsible for designing, building, and operating GDF's core data platform capabilities - pipelines, processing frameworks, storage layers, and service APIs that power downstream analytics and AI workloads across Walmart.
- Stay hands-on: write and review production code, prototype solutions to hard technical problems, and participate directly in design and code reviews rather than delegating all technical depth to the team.
- Own the engineering roadmap, technical execution, and delivery of scalable, high-throughput data services built on languages/frameworks including Java, Python, and Spark.
- Guide architecture and system design decisions across distributed data processing systems, batch and streaming pipelines, data lake/lakehouse storage, and enterprise integrations.
- Drive the design and evolution of Big Data capabilities - data ingestion, transformation, quality, observability, and governance - at the scale Walmart's platforms require.
- Partner with product managers, data scientists, ML engineers, and platform/security teams to deliver reliable, well-governed data capabilities that enable downstream analytics, reporting, and AI/ML use cases.
- Lead pragmatic integration of AI and GenAI capabilities into the data platform - e.g., feature pipelines for ML models, embeddings/vector search for retrieval, LLM-assisted data quality checks, and intelligent pipeline monitoring - wherever they create measurable engineering or business value.
- Ensure systems are designed for scalability, reliability, performance, observability, security, and cost efficiency, appropriate for petabyte-scale enterprise data platforms.
- Lead engineering execution across the full software development lifecycle - design, coding, testing, CI/CD, deployment, monitoring, incident management, and ongoing operational excellence.
- Champion DevOps, platform engineering, and automation best practices to improve engineering velocity, reduce toil, and support continuous delivery for a newly formed team building process and standards from scratch.
- Establish engineering standards through architecture reviews, design reviews, code reviews, testing strategy, observability practices, and production readiness reviews.
- Define and track engineering and data quality metrics - availability, latency, pipeline SLAs, data freshness, defect rates, deployment frequency, incident trends, and cost efficiency.
- Hire, mentor, and develop hands-on engineers, building a high-performing team culture grounded in craftsmanship, ownership, and continuous learning.
- Build strong cross-functional relationships across engineering, product, data science, and business teams to align priorities, manage dependencies, and remove blockers.
- Continuously evaluate emerging Big Data, cloud, and AI/ML technologies, applying them pragmatically where they improve platform reliability, engineering productivity, or business value.
What You'll Bring
- 12+ years of professional software engineering experience, including significant hands-on experience building and operating large-scale data platforms, distributed systems, and backend services.
- 4+ years of engineering leadership experience, including managing engineers and leading technical teams through complex delivery programs.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- Genuinely hands-on: comfortable writing, reviewing, and debugging production code - not just directing others. Strong proficiency in Java and Python is required; working knowledge of Spark for distributed data processing is expected.
- Strong exposure to Big Data technologies and ecosystems - Spark, Hadoop/HDFS, Hive, Kafka, or equivalent - including batch and streaming data processing, data pipeline design, and large-scale data transformation.
- Experience with data platform fundamentals: data modeling, ETL/ELT pipeline design, data quality and observability, data governance, and integration with enterprise data lakes/lakehouses (e.g., Delta Lake, BigQuery, Databricks).
- Strong experience with microservices architectures, distributed systems, event-driven patterns, API design, and enterprise system integration.
- Deep understanding of cloud-native engineering practices - CI/CD, containerization, Kubernetes or equivalent orchestration, infrastructure automation, and production operations.
- Strong knowledge of reliability engineering - observability, distributed tracing, logging, metrics, alerting,
- incident response, capacity planning, and fault tolerance for large-scale data systems.
- Full exposure to AI technologies in a production data platform context - hands-on experience integrating model APIs and GenAI/LLM-based tooling, working with embeddings/vector search, and applying MLOps practices (feature stores, model lifecycle, retraining pipelines). Comfortable using AI to strengthen data quality checks, pipeline monitoring, and engineering productivity, not just aware of it conceptually.
- Proven ability to translate ambiguous business/technical problems into clear execution plans, especially in a newly formed team without established process.
- Strong people leadership skills - hiring, coaching, mentoring, performance management - and a track record of building engineering culture from the ground up.
- Strong ownership mindset, sound technical judgment, high accountability, and comfort operating in a 0-to-1 environment.
About Walmart Global Tech
Imagine working in an environment where one line of code can make life easier for hundreds of millions of people. That’s what we do at Walmart Global Tech. We’re a team of software engineers, data scientists, cybersecurity expert's and service professionals within the world’s leading retailer who make an epic impact and are at the forefront of the next retail disruption. People are why we innovate, and people power our innovations. We are people-led and tech-empowered.
We train our team in the skillsets of the future and bring in experts like you to help us grow. We have roles for those chasing their first opportunity as well as those looking for the opportunity that will define their career. Here, you can kickstart a great career in tech, gain new skills and experience for virtually every industry, or leverage your expertise to innovate at scale, impact millions and reimagine the future of retail.
Walmart’s culture sets us apart, and we know being together helps us innovate, learn and grow great careers. This role is based in our [Bangalore/Chennai] office for daily work, with the flexibility for associates to manage their personal lives.
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.
Belonging
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 is—and feels—included, 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, we’re 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 Opportunities 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 inclusive of all people.
Minimum Qualifications...
Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Option 1: Bachelor's degree in computer science, computer engineering, computer information systems, software engineering, or related area and 5 years’ experience in software engineering or related area.Option 2: 7 years’ experience in software engineering or related area. 2 years’ supervisory experience.
Preferred Qualifications...
Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.
Master’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., 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.