1 day ago
Bengaluru, IndiaStaff+
Responsibilities
- Design, build, and operate large-scale batch and streaming data pipelines using Spark, Java, and Python.
- Apply software engineering practices including clean architecture, automated testing, CI/CD, code reviews, domain-oriented design, system design, and low-level design.
- Build and maintain services, APIs, and distributed systems supporting data pipelines and the broader platform codebase.
- Integrate embeddings, vector search, LLM-assisted data quality, anomaly detection, agentic monitoring, self-healing, and AI-assisted schema and lineage documentation.
- Partner with data scientists and ML engineers on feature pipelines, model-serving data paths, and MLOps infrastructure.
- Own data quality, observability, governance, reliability metrics, SLO/SLA practices, incident management, and post-incident reviews.
- Lead architecture and design reviews across data engineering and platform engineering.
- Set technical direction and best practices, mentor engineers, and influence broader data engineering standards.
- Evaluate emerging Big Data, cloud, and AI technologies and adopt them 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 for distributed data processing.
- 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 and observability, data governance, and lakehouse architectures such as Delta Lake, BigQuery, and Databricks.
- Hands-on experience integrating model APIs and GenAI/LLM tooling, building agentic workflows, using embeddings and vector search, and applying MLOps practices such as feature stores, model lifecycle, and retraining pipelines.
- Working knowledge of platform engineering, microservices, API design, Kubernetes or equivalent orchestration, CI/CD, and cloud-native practices.
- Strong distributed-systems, event-driven, asynchronous-processing, fault-tolerance, domain-oriented design, low-level design, system-design, testing, code-review, and design-pattern skills.
- Bachelor's or master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- Minimum qualifications include one of: a bachelor's degree in Computer Science and 4 years of software engineering or related experience; 6 years of software engineering or related experience; or a master's degree in Computer Science and 2 years of software engineering or related experience, plus 3 years of data engineering, database engineering, business intelligence, or business analytics experience.
- Additional experience with Go, C++, or Scala is preferred.
Benefits
- Incentive awards may be available based on performance.
- Benefits include maternity and parental leave, PTO, health benefits, and other company benefits.
- The role is based in the Bangalore or Chennai office for daily work, with flexibility to manage personal lives.
Tech Stack
Apache AirflowApache HadoopApache HiveApache KafkaApache SparkC++DatabricksGoGoogle BigQueryJavaKubernetesPythonScala
Categories
Data 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.