Pyspark Data Engineer

Expertise in Data Architecture, Data Strategy and Roadmap for
large and complex organization and systems and implemented
large scale end-to-end Data Management & Analytics solutions
Experience in transforming traditional Data Warehousing
approaches to Big Data based approaches and proven track
record of managing risks and data security
Expertise with DW Dimensional modeling techniques, Star &
Snowflake schemas, modeling slowly changing dimensions and
role playing dimensions, dimensional hierarchies, and data
classification
Experiences in cloud native principals, designs and deployments.
Extensive experience working with and enhancing Continuous
Integration (CI) and Continuous Development (CD) environments
Expertise in Data Quality, Data Profiling, Data Governance, Data
Security, Metadata Management, and Data Archival
Define workload migration strategies using appropriate tools
Drive delivery in a matrixed environment working with various
internal IT partners
Demonstrated ability to work in a fast paced and changing
environment with short deadlines, interruptions, and multiple
tasks/projects occurring simultaneously
Must be able to work independently and have skills in planning,
strategy, estimation, scheduling,
Strong problem solving, influencing, communication, and
presentation skills, self-starter
Experience with data processing frameworks and platforms
(Hadoop, Presto, Tez, Hive, Spark etc.)
Hands on experience in work with bigdata platforms and related
programming languages (e.g. Linux, Python, PySpark, GIT,
Jenkins)