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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, test, and deploy scalable, fault-tolerant data engineering solutions handling petabytes of data at Walmart scale.
Develop and optimize high-performance Apache Spark and big data ETL pipelines primarily using Databricks and related technologies like Kafka, Airflow.
Collaborate with cross-geographical engineering and business teams to deliver robust data products, perform root cause analysis, and mentor junior engineers.
Minimum Requirements
11+ years of hands-on programming experience in Python.
7+ years of experience designing and developing large-scale, fault-tolerant data pipelines using big data technologies (Spark, Kafka, Airflow, Hadoop ecosystem).
Bachelor’s or Master’s degree in Computer Science or related technical field.
Strong expertise in database fundamentals (SQL, PL/SQL, stored procedures) and data warehousing/ETL concepts.
Ideal Candidate Profile
Experienced in system design, distributed systems, and building petabyte-scale, high-concurrency data pipelines with zero data loss and real-time monitoring.
Able to lead end-to-end product development incorporating test-driven, behavior-driven, and configuration-driven development practices.
Demonstrated ability to collaborate across teams and geographies and mentor junior engineers with a platform-driven approach.