1 day ago
Bengaluru, IndiaStaff+
Responsibilities
- Design, build, and operate large-scale batch and streaming data pipelines.
- Develop and maintain platform services, APIs, and distributed systems supporting data pipelines.
- Apply software engineering, system design, domain-oriented design, low-level design, testing, code review, and CI/CD practices.
- Integrate embeddings, vector search, LLM-assisted data quality, anomaly detection, agentic monitoring, and AI-assisted schema and lineage documentation.
- Build feature pipelines, model-serving data paths, and data infrastructure supporting MLOps.
- Own data quality, observability, governance, SLO/SLA performance, incident management, and operational excellence.
- Lead architecture and design reviews across data engineering and platform engineering.
- Set technical direction, mentor engineers, and influence broader data engineering standards.
- Evaluate and adopt Big Data, cloud, and AI technologies where they improve reliability, productivity, or business value.
Requirements
- 8+ years of professional software engineering experience with significant hands-on data engineering at scale.
- Strong proficiency in Java and Python and strong working knowledge of Spark are required.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- Minimum qualifications include either a bachelor's degree in Computer Science plus 4 years of software engineering experience, 6 years of software engineering experience, or a master's degree in Computer Science plus 2 years of software engineering experience, along with 3 years of data engineering, database engineering, business intelligence, or business analytics experience.
- Deep experience with Spark, Hadoop/HDFS, Hive, Kafka, workflow orchestration such as Airflow, batch and streaming processing, and large-scale data transformation.
- Experience with data modeling, ETL/ELT pipeline design, data quality, observability, data governance, and lakehouse architectures such as Delta Lake, BigQuery, and Databricks.
- Hands-on experience with model APIs, GenAI/LLM tooling, agentic workflows, embeddings, vector search, and MLOps practices including feature stores, model lifecycle, and retraining pipelines.
- Working knowledge of microservices, API design, Kubernetes or equivalent orchestration, CI/CD, and cloud-native practices.
- Strong distributed-systems, event-driven, asynchronous-processing, fault-tolerance, system-design, domain-oriented-design, and low-level-design skills.
- Strong software engineering craftsmanship, technical judgment, autonomy, and ability to translate ambiguous problems into execution plans.
Benefits
- Performance-based incentive awards, maternity and parental leave, PTO, health benefits, and other benefits.
- Daily work is based in the Bangalore or Chennai office, with flexibility to manage personal lives.
Tech Stack
Apache AirflowApache HadoopApache HiveApache KafkaApache SparkC++DatabricksGoGoogle BigQueryJavaKubernetesPythonScala
Categories
BackendData Engineering
About Walmart
Walmart is a global omnichannel retailer that sells groceries, general merchandise, and services through Walmart and Sam's Club stores and online marketplaces for consumers and small businesses. Its model spans physical retail, e-commerce, advertising, and a vast supply chain, plus pharmacy, health, and financial services. Founded in 1962 and headquartered in Bentonville, Arkansas, Walmart Inc. is a public company on the NYSE (WMT) operating in the U.S. and multiple international markets.