Data Engineer with Graph data Experience

Need Data engineer with Knowledge Graphs (Stardog) Resource Requirement

Location: NYC but also open to east cost (New York area , Boston , Washington DC and North Carolina)
High level Skill: Advance Graph data & processing technology skills with program management

The candidate will be a consultant with strong room presence who can take complex business problems in the FS domain and convert them to data problems using Knowledge Graph Technology, Visualizations, Data Engineering and Data Science techniques. < /p>

• Lead Data Engineering engagements for Top Global FS clients.
• Play the role of a thought leader and Lead Solution Architect to define the next generation Knowledge Graph / Analytic solutions.
• Consult to Chief Data Officers, Chief Analytics officers, Chief Marketing Officers by demonstrating deep understanding around one or more problem domains in Sales and Marketing, Data Science, Analytics, Data Warehousing, and Strategy.
• Own the client relationships specific to the engagement
• Provide leadership and mentor junior consultants in the engagement team
Basic Qualifications:
• Bachelor’s degree in Computer Science / or a quantitative field such as Mathematics, Statistics, Applied Math, Economics
• 7+ years of experience within the Data Analytics Space.
• Strong Consulting experience with domain focus in one or more areas in Banking, Capital Markets, Insurance , Payments
• Hands on experience in at-least one of the following
o Knowledge Graphs (Stardog) , Neo4J or any other KG technology
o Apache Nifi ,Python , Apache Spark , Data Warehousing and Governance
o Data Visualization tools like Qlikview , Tableaue , Platfora , Datameer
• Ability to interact at the highest levels in client organizations
Preferred Qualifications:
• MBA/ BS, Data Science / Data Engineering Graduate degree is preferred
• Big Data and or Machine Learning Certifications. Apache Spark
• Experience working for a consultancy or large service provider
• An understanding of Big Data technologies and their applicability in quantitative techniques.
Thanks & Best Regards
Ph: 501-438-9567
Fax: 501-295-3340


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