Data Engineer - Pyspark

Qualifications and ExperienceExpertise in Data Architecture, Data Strategy and Roadmap for large and complex organization and systems and implemented large scale end-to-end Data Management & Analytics solutionsExperience in transforming traditional Data Warehousing approaches to Big Data based approaches and proven track record of managing risks and data securityExpertise with DW Dimensional modeling techniques, Star & Snowflake schemas, modeling slowly changing dimensions and role playing dimensions, dimensional hierarchies, and data classificationExperiences in cloud native principals, designs and deploymentsExtensive experience working with and enhancing Continuous Integration (CI) and Continuous Development (CD) environmentsExpertise in Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, and Data ArchivalDefine workload migration strategies using appropriate toolsDrive delivery in a matrixed environment working with various internal IT partnersDemonstrated ability to work in a fast paced and changing environment with short deadlines, interruptions, and multiple tasks/projects occurring simultaneouslyMust be able to work independently and have skills in planning, strategy, estimation, schedulingStrong problem solving, influencing, communication, and presentation skills, self-starterExperience 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)#J-18808-Ljbffr