DISTINGUISHED, SOFTWARE ENGINEER

Design and optimise large-scale batch data pipelines using Spark, Hive, or equivalent — covering feature computation, aggregation, transformation, and materialization into both offline and online stores.

Define offline store schema and partitioning strategies (e.g., Parquet/ORC on cloud object storage) optimised for point-in-time correct training dataset generation.

Establish pipeline reliability and observability standards: data freshness SLOs, quality checks at ingestion, deduplication, late-arrival handling, and lineage tracking.

Provide guidance on orchestration and scheduling of batch workloads (Airflow or equivalent), including dependency management, SLA monitoring, and failure recovery.

Architect and optimise online feature serving infrastructure targeting high QPM at consistently low latency (p99 in single-digit milliseconds), across multi-region, multi-cloud deployments.

Design data access layers over low-latency stores (Cassandra, Redis, Spanner, or equivalent) — including read path optimization, caching strategy, connection pool management, and circuit breaking.

Define online serving reliability patterns: multi-DC failover, graceful degradation, bulkhead isolation, and zero-downtime schema migrations.

Establish capacity planning and load testing practices for online stores; translate traffic forecasts into storage and compute provisioning recommendations.

Lead the design and evolution of the platform's Java and Python SDKs — from the current thick SDK (heavy direct data store coupling) to a thin SDK that handles only routing table fetching, feature name parsing, and request dispatch.

Own the Java SDK's API contract, versioning strategy, backward compatibility guarantees, and deprecation policy (including serializer migration across major versions).

Define ergonomic, well-documented Python SDK interfaces for data science and ML engineering consumers, ensuring consistency with the Java SDK's service contract.

Establish SDK release governance: semantic versioning, changelog discipline, dependency management, and multi-version co-existence strategies.

Key responsibilities for this role include:

10+ years of production software development experience, with demonstrable ownership of complex, distributed systems.

Java (Expert): Concurrency primitives ( AtomicReference , CAS, CompletableFuture , ForkJoin ), SDK/library design, API versioning, backward compatibility guarantees, and dependency management.

Python (Strong): Production-grade library and SDK design for data science or ML engineering consumers; idiomatic async client patterns; packaging and dependency management.

Strong data modelling instincts across relational, wide-column, key-value, and columnar storage paradigms.

Experience with observability tooling: distributed tracing ( OpenTelemetry ), structured logging, metrics (Prometheus/Grafana or equivalent), and SLO-based alerting.

Experience deploying and operating production services on Kubernetes at scale (GKE, AKS, or equivalent).

Familiarity with GCP and/or Azure infrastructure: managed storage services, multi-cloud networking, IAM/RBAC, and cloud-native observability tooling.

Understanding of CI/CD pipeline design for data and ML workloads — including pipeline testing strategies, staged rollouts, and data migration patterns.

Proven experience designing and operating services at high QPM with p99 latency targets in the low-millisecond range, across distributed, multi-region infrastructure.

Deep expertise in low-latency data stores:

Cassandra: Data modelling, partition key design, consistency level trade-offs, compaction strategies, multi- datacenter replication, driver internals (DataStax Java Driver).

Redis: Eviction and expiry policies, cluster mode, pipelining, client-side connection management (Jedis, Lettuce).

Expert-level understanding of distributed systems fundamentals: CAP theorem, consistency models, replication topologies, partitioning strategies, and eventual consistency trade-offs.

Deep expertise in reliability engineering for online systems: circuit breakers, exponential backoff with jitter, bulkhead patterns, rate limiting, local vs. remote DC failover, and graceful degradation under store-side pressure.

Experience with gRPC service design at scale: service contract definition, proto schema evolution, deadline propagation, streaming patterns, and observability (per-RPC latency histograms, error rate tracking).

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 office for daily work, with the flexibility for associates to manage their personal lives.

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.

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.