Essential Technical Skills:
Big Data Technologies: Extensive hands-on experience with Hadoop, Spark, Hive, and Trino for processing petabyte-scale datasets. Proven ability to diagnose and resolve data skew, resource limitations, scalability challenges, and job failures in production environments.
Apache Spark Expertise: Deep understanding of Spark architecture including executors, tasks, stages, and DAG execution. Demonstrated proficiency in performance tuning techniques such as partitioning strategies, caching, broadcast joins, and optimization of large-scale data processing jobs.
SQL Mastery: Advanced proficiency in complex SQL including window functions, multi-table joins, aggregations, and query optimization. Experience handling edge cases involving NULLs, duplicates, and ordering in production environments.
Cloud Technologies: Strong experience with AWS services including S3, EMR, Glue, Lambda, Athena, EKS, and serverless architectures. Practical knowledge of file format optimization, consistency management, and cloud-based data processing workflows.
Programming (Python/Scala): Proficiency in writing clean, modular, and performant code using Python or Scala. Strong understanding of functional programming concepts (immutability, higher-order functions), collections, concurrency, and memory management for scalable data processing.
AI Tool Proficiency: Hands-on experience with AI development tools (GitHub Copilot, Q Developer, ChatGPT, Claude, etc.) and AI workflow design. Proven ability in prompt engineering and leveraging AI coding assistants for enhanced productivity.
Agile Methodology & Change Management: Extensive experience with Scrum, Kanban, and continuous improvement practices. Demonstrated experience leading teams through AI adoption, technology transformation, and workflow optimization initiatives.
System Design & Architecture: Strong system design experience with ability to architect scalable, distributed data processing solutions and enterprise-level applications.
Object-Oriented Development: Strong experience in object-oriented programming principles, design patterns, and software engineering best practices.
Data Storage Technologies: Strong experience with modern data storage solutions, database technologies, and data modeling approaches for both relational and NoSQL systems.
Performance Tuning & Optimization: Demonstrated expertise in identifying bottlenecks and optimizing application and data processing performance across the full stack.
DevOps & CI/CD: Strong experience with DevOps practices, continuous integration, continuous deployment pipelines, and infrastructure as code.
Software Security: Strong understanding of security best practices, secure coding principles, and application security across all layers.
Data Analysis & Insights: Ability to interpret AI-generated insights and data-driven metrics, translating them into actionable technical improvements and measurable business value.
Education/Experience Requirements:
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Bachelor’s degree in Computer Science, Information Systems or related discipline with at least 7 years of related experience, or equivalent training and/or work experience.
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Strong system design experience
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Strong experience in object-oriented development
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Strong experience with cloud technologies
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Strong experience in data storage technologies
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Strong experience in performance tuning and optimization
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Strong experience in DevOps and CI\CD technologies
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Strong experience test automation and unit testing
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Strong experience software security