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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, test, and deploy large-scale, high-performance data pipelines and ETL solutions using Spark and related Big Data technologies, handling petabytes of data.
Perform root cause analysis on data and processes, and optimize data architectures and workflows, primarily leveraging Databricks and distributed systems.
Collaborate with cross-functional teams globally, mentor junior engineers, and drive best practices in software development and data engineering.
Minimum Requirements
11+ years of hands-on object-oriented programming experience in Python.
7+ years experience designing and developing scalable data pipelines using Big Data technologies (e.g., Apache Spark, Kafka, Airflow).
Strong expertise in ETL design, Data Modeling, Data Warehousing, and distributed system design.
Bachelor’s or Master’s degree in Computer Science or a related technical field.
Ideal Candidate Profile
Experienced in building petabyte-scale, fault-tolerant, and highly scalable data systems with zero data loss and sub-second latency.
Skilled in end-to-end product development with strong system design, failure handling, and monitoring capabilities.
Proven ability to collaborate internationally, mentor teams, and balance trade-offs between performance, cost, and reliability in cloud environments.