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Remote role, popular Data Engineer title, and mid-level (5+ years) experience increase competition.
Role requires specialized AWS data lakehouse and big-data skills, moderately limiting cross-industry fit.
Explicit 5+ years requirement plus many mandatory AWS, Spark, and data lakehouse technologies makes shortlisting strict.
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Design, build, and maintain scalable and low-latency data systems leveraging AWS services such as EMR, DynamoDB, Aurora, PostgreSQL, and Redshift.
Implement and operate AWS data lakehouse architectures using Step Functions, Lambda, and EventBridge to support analytical platforms.
Develop data pipelines and applications primarily using Apache Spark, Python, and other big data technologies.
5+ years of software development experience focused on analytical platforms.
3+ years of experience in data platforms or big data ecosystems.
Strong expertise with AWS technologies including EMR, DynamoDB, Step Functions, Lambda, EventBridge, and experience with Apache Spark, PostgreSQL, Apache Iceberg, and Python.
Work Experience Required: 5+ years software development, 3+ years data platforms
Experienced in architecting and implementing AWS data lakehouse solutions with demonstrated hands-on skills.
Comfortable working with event-driven and real-time streaming data architectures.
Proficient in building complex data pipelines combining AWS managed services and open-source big data tools.