Design and build batch and streaming data pipelines for ingestion and analytics.
Own end-to-end delivery of complex data initiatives: architecture, deployment, monitoring.
Develop and evolve the data platform with modern cloud-native tech.
Automate data operations: validation, quality checks, alerts, backfills, recovery.
Optimize cost, performance, and reliability of data workloads.
Partner with Data Science, Product, and Engineering to translate requirements into solutions.

🎯 Requirements

5+ years building production-grade data platforms and pipelines.
Python or Scala for data processing; SQL for analytics.
Distributed data processing with Spark; performance tuning.
Building data solutions on AWS (EMR, Lambda, S3, etc).
Data modeling and warehousing concepts, including partitioning.
Monitoring, alerting, incident response, and reliability of pipelines.

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