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Staff Data Engineer – Finance Data Lake

  • GE Digital
  • Experienced
  • Posted 12/10/2016 8:47:09 PM
  • 2740826
  • Job Function: Information Technology
  • Business Segment: Digital Information Technology & Digital Thread
Location(s): Hungary; Budapest


About Us:
GE is the world’s Digital Industrial Company, transforming industry with software-defined machines and solutions that are connected, responsive and predictive. Through our people, leadership development, services, technology and scale, GE delivers better outcomes for global customers by speaking the language of industry. Additional introduction… It is not about your career… it is not about your job title… it is about who you are…. It is about the impact you are going to make on the world. You want to go into uncharted waters… do things that haven’t been done to make yours and someone else's life better. GE has been doing that for decades! We will continue to do so! We are the world’s digital industrial company.

GE is diversity. We aim to employ the worlds’ brightest minds to help us create an unlimited source of ideas and opportunities. We believe in hiring talented people of varied backgrounds, experiences and styles - people like you!

Role Summary:
The Staff Data Engineer is a key thought leader within the Finance Data Lake team responsible for architecting solutions to migrate critical ERP Finance data from GE Business platforms to the Data Lake platform for analytics and reporting. The candidate should have cutting-edge ELT/ETL expertise with data modeling, real-time big data processing and data manipulation as well as a fundamental understanding of end-to-end business processes and ERP systems.

Essential Responsibilities:
• Provide thought leadership on data integration spanning the relational and big data landscape, representing the multitude of GE Finance functional areas and key business processes including AP, AR, GL, etc.
• Maintain a strong understanding of existing and upcoming ingestion technology (e.g. Talend, HVR, Spark), drive innovation in the space, execute proof of concepts and oversee the execution of delivery.
• Architect and design ELT/ETL Strategy, analyze data models and optimize data ingestion processes for the Data Lake to ensure near-real time delivery.
• Influence a team of architects and developers on high-volume data extraction, without compromising on Data Quality and ensure accuracy of extracted data.
• Ability to query data both in source and destination and anticipate corrective measures; measure and publish data movement metrics on a sustainable basis
• Performs impact analysis against metadata manager directories, creates and maintains data lineage and provides leadership on Data Governance.
• Ensures that plans for assigned applications integrate effectively with other aspects of the technical infrastructure, promotes a loosely-coupled software architecture in an Agile framework
• Engages with Project Managers and Senior Leaders to provide estimates for project plans and costing.


Qualifications/Requirements:
• Bachelor's Degree in Computer Science, Finance or Industrial or Mechanical Engineering
• Strong work experience in ETL/ELT, data modeling and design of OLTP, OLAP systems
• Strong experience with Big Data tech stack like Greenplum and HDFS, ETL tools like Talend and HVR, real-time and in-memory data processing with Spark, Kafka, Hive etc.
• Prior experience managing a global team of architects and developers in a fast-paced environment


Desired Characteristics:
• Functional understanding of Financial systems and ERP software, exposure to Sourcing and GL modules
• Experience with Cloud computing
• Confronts difficult circumstances in creative ways, balances multiple and competing priorities and executes accordingly
• Strong interpersonal skills, with ability to professionally interact with a diverse blend of
personalities to reach resolution and maintain strong relationships
• Strong attention to detail
• Able to articulate technical concepts in non-technical terms that appeal to business stakeholders

#DTR




Locations: Hungary; Budapest
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