Senior Data Engineer - Spark & AWS

Engineer

Senior Data Engineer – Spark & AWS

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  • Date posted
    July 15, 2026
  • Expiration date
    October 15, 2026
  • Application ends
    October 15, 2026

As a Data Engineer, you will build and optimize the data infrastructure that powers the platform’s analytics capabilities. You’ll design scalable data pipelines, develop distributed processing jobs, and ensure high-quality data is available to support AI-driven anomaly detection and advanced analytics. This role is ideal for engineers who enjoy working with large datasets, cloud technologies, and modern data engineering frameworks.

Responsibilities:
  • Design, build, and maintain scalable data pipelines that ingest telemetry, log, and configuration data
  • Develop distributed data processing applications using Apache Spark
  • Build and optimize ETL/ELT workflows within a cloud-based data lake
  • Collaborate with Data Scientists and AI Engineers to prepare and deliver data for analytics and machine learning workloads
  • Optimize pipeline performance, scalability, and reliability
  • Ensure data quality through monitoring, validation, and troubleshooting
  • Partner with Platform Engineering to deploy and support data processing applications in AWS
  • Contribute to data architecture decisions and engineering best practices
Requirements
  • 5+ years of experience in Data Engineering or a related field
  • Strong experience developing distributed processing applications with Apache Spark
  • Experience with a second programming language such as Scala (preferred), Java, or another compiled language
  • Experience designing and building scalable ETL/ELT pipelines
  • Hands-on experience working with AWS cloud services
  • Experience with cloud-based data lakes and large-scale datasets
  • Strong understanding of distributed systems and data engineering best practices
  • Proficiency in Python
Preferred Qualifications:
  • Experience working with telemetry, log, or operational data
  • Experience supporting AI, machine learning, or anomaly detection initiatives
  • Experience working in Agile development environments
  • Familiarity with streaming data technologies
  • Knowledge of graph-based data models or network-related data
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