Data Engineer

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Company Overview

A leading global technology company is seeking a Data Engineer to join its Media, Graphics, and Compute Technologies organization. The team is responsible for delivering large-scale data collection, warehousing, analytics, and monitoring solutions that support data-driven decision-making across multiple digital services. By leveraging advanced Data Engineering, Generative AI, and Machine Learning technologies, the organization provides high-performance analytics platforms and operational insights at massive scale.

The organization is looking for a talented and dedicated Data Engineer to contribute to the design, enhancement, and development of high-volume data processing pipelines and next-generation analytics platforms. This role offers the opportunity to work in a dynamic, agile environment alongside experienced engineers and cross-functional teams focused on engineering excellence, innovation, and scalable data solutions.

The successful candidate will play a key role in building and maintaining modern data infrastructure, applying Generative AI and Machine Learning technologies, and developing systems that enable actionable insights and operational intelligence across large-scale services.

Key Responsibilities

• Collaborate with data scientists and cross-functional teams to define and improve performance metrics that provide valuable business insights.
• Build and maintain real-time data ingestion pipelines for large-scale data processing.
• Develop real-time applications that support operational monitoring and analytics.
• Design and maintain batch ETL/ELT workflows that populate and optimize enterprise data warehouses.
• Apply Generative AI and Retrieval Augmented Generation (RAG) techniques to enhance data analytics capabilities.
• Utilize Machine Learning technologies to support anomaly detection and intelligent monitoring systems.
• Tune and scale Apache Kafka producer and consumer workloads, Spark Structured Streaming applications, and Flink-based processing systems.
• Manage and monitor large-scale data collection and analytics pipelines in cloud environments.
• Perform capacity planning and infrastructure scaling for applications running on Kubernetes.
• Troubleshoot production issues and conduct performance analysis of distributed systems.
• Partner with engineering and business teams to ensure high availability, reliability, and performance of data platforms.
• Stay current with emerging data engineering technologies and implement relevant innovations.

Required Qualifications

• Bachelor’s degree in Computer Science or equivalent professional experience.
• Experience building large-scale distributed systems using Java, Python, or similar programming languages.
• Strong proficiency in SQL.
• Experience with data warehouse architectures and dimensional data modeling.
• Demonstrated ability to troubleshoot and perform performance analysis on large-scale distributed systems.
• Strong collaboration and communication skills with the ability to work effectively across teams and complex technical environments.
• Hands-on experience with Docker and Kubernetes.

Preferred Qualifications

• Production experience with Apache Kafka, Spark, or Flink.
• Working knowledge of Trino or similar distributed query engines.
• Experience building multi-agent AI systems or agentic workflows.
• Familiarity with Retrieval Augmented Generation (RAG) techniques integrated with Large Language Models (LLMs).
• Experience creating and consuming Model Context Protocol (MCP) services.

Disclaimer

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