As a Senior Data Engineer, you'll be part of a team of smart, highly skilled technologists who are passionate about learning and supporting cutting-edge technologies such as Spark, Scala, Pyspark, Databricks, Airflow, SQL, Docker, Kubernetes, and other Data engineering tools. These technologies are deployed using DevOps pipelines leveraging Azure, Kubernetes, Jenkins and Bitbucket/GIT Hub.
Responsible to assemble large, complex sets of data that meet non-functional and functional business requirements.
Responsible to identify, design and implement internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes.
Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using Azure, Databricks and SQL technologies
Responsible for the transformation of conceptual algorithms from R&D into efficient, production ready code. The data developer must have a strong mathematical background in order to be able to document and maintain the code
Responsible for integrating finished models into larger data processes using UNIX scripting languages such as ksh, Python, Spark, Scala, etc.
Produce and maintain documentation for released data sets, new programs, shared utilities, or static data. This must be done within department standards
Ensure quality deliverables to clients by following existing quality processes, manually calculating comparison data, developing statistical pass/fail testing, and visually inspecting data for reasonableness: the requirement is on-time with zero defects
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