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Technical Experience Required: Python, Apache Spark, and Hadoop

The client is looking for a Big Data Engineer to build and maintain an infrastructure for delivering customer insights from structured and unstructured data sources. The Data Engineer will implement analytical solutions with a focus on collecting, managing, modeling, analyzing, and visualizing data and develop batch and real-time processes to move data. Work in an Agile Scrum driven environment to deliver new and innovative products for Analytics customers, and keep up-to-date with relevant technology in order to maintain and improve functionality. Must be able to work across multiple divisions and teams to ensure the end result of the product.

Responsibilities:
  • Ability to work with senior IT and Business leaders providing technical guidance related to data architecture, data models and metadata management
  • Works closely with database teams on topics related to data requirements, cleanliness, and accuracy
  • Interacts with Business divisions to understand all data requirements to develop business insights and translates them into data structures and data model requirements to IT
  • Codes, test, and documents new or modified data systems to create robust and scalable applications for data analytics
  • Develop standards and processes for integration projects and initiatives
  • Collects, parses, manages analyzes and visualizes large sets of data using multiple platforms
  • Ensures that data pipelines are scalable, repeatable, secure, and can serve multiple users within the company

Qualifications
  • Bachelor's or Master's Degree in technical or business discipline or related experience; Master's Degree preferred
  • Experience of working with Big Data Systems such as Hadoop, Hive, Spark, etc.
  • Strong SQL Skills
  • Programming/scripting experience with languages such as Scala or Python
  • Demonstrated ability to manage and prioritize workload and roadmaps
  • Solid written and verbal communication skills
  • Familiarity with AWS solutions such as EMR, S3, and Redshift
  • 3+ years of professional experience in data engineering or comparable position
  • 5+ years of experience with advanced data management systems (Teradata, Hadoop)
  • 5+ years of experience in developing applications in high volume data staging/ETL environments and is proficient in advanced SQL experience
  • Technical Experience Required: Python, Apache Spark, and Hadoop
  • A clear understanding of different data domains in operations and has experience in master data management
  • Strong analytical and problem-solving experience paired with the ability to develop creative and efficient solutions; tolerance in dealing with bad quality data
  • Knowledge of developing and maintaining a formal document that describes data and data structures including data modeling
  • Comfortable working in an unstructured environment that will require self-starters/motivators to achieve benchmarks
  • Agile and collaborative environment working to support the whole division
  • Nice to have technical experience: JIRA, AWS Glue, Redshift

Last updated on Aug 8, 2019

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