Data Engineer – AI, Java, Python, Spark

• Develop, test and maintain high-quality, production-ready software

• Design and implement large-scale data pipelines and distributed processing systems

• Build scalable cloud-native services and platforms

• Provide technical leadership for cross-team initiatives and complex engineering projects

• Design and develop reusable libraries, frameworks and platform components

• Optimize distributed data processing workloads for performance, scalability and reliability

• Work with Databricks, Apache Spark and Snowflake data platforms

• Develop and deploy applications using Python and/or Java

• Build and operate containerized workloads using Kubernetes and cloud-native technologies

• Design and implement GenAI/LLM-based applications and services

• Use LangChain and LangGraph for LLM orchestration and agentic workflows

• Collaborate with data scientists, software engineers, architects and product teams

• Establish engineering best practices around testing, observability, reliability and deployment

Requirements

• 5+ years of professional software/data engineering experience

• Strong hands-on experience with Python and/or Java

• Strong experience with Apache Spark and distributed data processing

• Experience with Databricks and/or modern lakehouse platforms

• Experience with Snowflake or comparable cloud data warehouses

• Practical experience with Kubernetes and cloud-native technologies

• Experience designing and maintaining large-scale data pipelines

• Strong understanding of distributed systems, scalability and production engineering

• Experience developing ML/AI or GenAI applications

• Experience with LLM-based applications, RAG, AI agents or LLM orchestration

• Familiarity with LangChain, LangGraph or similar GenAI frameworks

• Strong software engineering fundamentals including testing, code quality and system design

Core Competencies

Demonstrates expertise in developing and maintaining high-quality software, with a strong focus on building scalable cloud-native services and optimizing distributed data processing. Proficient in Python, Java, and modern data platforms, with a solid understanding of GenAI applications and engineering best practices.

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