Manager, Data Platform Engineering
April 2
Amazon Redshift
Apache
AWS
Azure
Cloud
Distributed Systems
Google Cloud Platform
Java
Kafka
MySQL
Postgres
Python
Scala
Spark
Go
Description
• Lead a team focused on building a robust and scalable foundation for data • Responsible for detailed architecture, POC, design, advising and hands-on implementation of complex systems • Own and architect scalable solutions that are implementable with principles of extensibility, scalability, modular and easy to use with generalization principles • Help create and implement data governance structures that ensure adherence and adoption of data policies • Champion platform standards, tooling, and processes
Requirements
• Minimum 5+ years of experience building and leading a team of high-performing data platform engineers • Experience building and deploying products that rely on large-scale distributed systems in Python or Go, Scala/Java, or other similar languages • Experience with large-scale, distributed systems design and development with an understanding of scaling, replication, consistency, and high availability • Experience in defining and developing high-volume, horizontally scalable architectures • Experience with system software design and development with an understanding of computer architecture, storage, network, and IO subsystems • Experience with Big Data query engines such as Hive, Presto, Trino, Spark • Experience with data stores such as Redshift, MySQL, Postgres, Snowflake, etc. • Experience using Realtime technologies like Apache Kafka, Kinesis, Flink, etc. • Technical knowledge of Cloud Platforms (AWS, GCP, Azure) and open-source technologies • Background in performance tuning, identifying performance bottlenecks, and implementing performance optimizations • Prefer BS, MS, or Ph. D. in Computer Science with 6+ years of proven relevant industry experience • Can switch fluently between player/coach model (hands-on programmer with a good knowledge of data-structures and CS algorithms)
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