We currently have an exciting opportunity for a hands-on Director, Data Engineering to lead the design and development of data and analytics solutions on an AWS hosted platform, build and motivate a high performing team of engineers, advise and inform the executive team regarding technology solutions that can maximize business value, and provide necessary leadership to establish the strategic framework for success.
Lead the design and implementation of scalable ETL and data processing systems to handle the big data ecosystem including data collection, processing, ETL and Data Lake.
Build internal Reporting and Analytics platform on top of our Big Data Lake.
Manage data infrastructure to grow and support the team as well as the organization as it relates to Data Platforms.
Be a trusted partner for Data analysts. Build and maintain data infrastructure, such as Redshift, Hive and Spark, and enable analysts to be more efficient and effective in their jobs.
Partner with teams across HBO to ingest, store and enrich data throughout the organization within the enterprise data lake and underlying data marts.
Establish the technical direction for the team, driving the necessary changes and making appropriate technology choices working collaboratively with the Strategy and Architecture team.
Collaborate with Product Management team to define technical requirements and design clarity based on the business requirements.
REQUIREMENTS
BS/MS/PhD in Computer Science or related field or equivalent experience
At least 7 years of experience in data engineering and data management
At least 5 years’ experience with leading big data technologies
7+ years of experience designing data warehouse/data lake and ETL architectures with big data ecosystem such as Spark, Hive, Storm, Sqoop, Kafka, Hbase and HDFS
Experience managing or leading small to medium sized engineering teams in a dynamic environment
3+ years of experience with the AWS eco-system, toolsets and deployment architecture
3+ years of leading modern development approaches (containerization, cloud, continuous delivery, micro-services)
Solid understanding of real time and batch data processing framework such as Hadoop, Spark etc.
Experience with SQL/NOSQL systems such as MongoDB , Cassandra or Redshift
Understanding of data flows, data architecture, ETL, and processing of structured and unstructured data
Ability to learn new technologies and evaluate multiple technologies to solve a problem
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