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)