Data Engineer - Pyspark

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).