Sr. Data Engineer

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Company Overview

A leading global technology company is focused on building innovative products, applications, and platforms used by millions of customers worldwide. Its cloud services organization develops scalable and reliable data infrastructure that powers seamless access to content across a broad ecosystem of applications and devices. By delivering accurate, integrated, and high-quality data capabilities, the organization enables data-driven decision-making and continuous product improvement at global scale.

The organization is seeking a Sr. Data Engineer, iCloud to help drive the future of large-scale cloud products and services. This role offers the opportunity to work on highly impactful data infrastructure that supports critical business and product decisions while improving user experiences across a broad suite of applications and platforms.

The successful candidate will have strong expertise in distributed data processing, large-scale data engineering, and data architecture. This position requires a passion for solving complex data challenges, building scalable systems, and leveraging data to improve products, applications, and platform capabilities.

Key Responsibilities

• Design, build, and maintain efficient, scalable, and adaptable data pipelines for processing structured and unstructured data.
• Own, manage, and enhance large-scale datasets related to product and platform interactions.
• Develop forward-looking data solutions that integrate effectively with existing systems and technologies.
• Evaluate and implement modern data technologies to meet evolving business and technical requirements.
• Partner with cross-functional teams to understand how technical decisions impact business outcomes.
• Deliver data frameworks and platforms that improve quality, scalability, and operational efficiency.
• Collaborate with data experts and engineering teams to create solutions that enhance organizational decision-making.
• Ensure data infrastructure remains reliable, accurate, timely, and scalable for a variety of use cases.

Required Qualifications

• 8+ years of experience working with Apache Spark and other distributed data technologies such as Hadoop, Presto, Flink, or Druid.
• Strong programming skills in at least one of the following languages: Java, Python, or Scala.
• Deep expertise in data principles, data architecture, data modeling, and SQL.
• Strong analytical and problem-solving abilities with exceptional attention to detail.
• Experience solving complex and loosely defined technical challenges.
• Experience working within cross-functional and matrixed organizations.
• Excellent communication and collaboration skills with the ability to lead technical discussions and influence strategy.
• Familiarity with cloud technologies and services, including AWS resources such as S3, EC2, and RDS.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field, or equivalent practical experience in software or data engineering.

Preferred Qualifications

• Experience with cloud computing platforms such as AWS or Google Cloud.
• Experience building stream-processing applications using technologies such as Apache Flink, Spark Streaming, Apache Storm, or Kafka Streams.
• Experience working with search platforms such as Elasticsearch or Solr.
• Experience with NoSQL databases such as HBase, Cassandra, or MongoDB.
• Experience designing and building distributed, high-volume data services.

Disclaimer

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