Graph Data Engineer / Analyst

Bridgecor LLC

Where Diversity Meets Engineering

Job Description

We are looking for a Graph Data Engineer / Analyst to join our dynamic and growing team. We specialize in developing data science applications that are used for the identification of fraud, non-compliance, and other types of criminal activities. The ideal incumbent will have experience designing, building, and analyzing graph databases using tools such as SQL, Cypher, Java, Bash, Hadoop, Spark, and Elastic.

As a Data Engineer, you will work with data scientists and machine learning engineers to build international-scale artificial intelligence systems to identify and refer civil and criminal forms of fraud and non-compliance.

You will work on data transformation projects, data warehouses, proof of concepts, and machine learning systems to drive automation and serve data to downstream applications and end-users. You will build data pipelines, knowledge graphs, and Machine Learning algorithms to empower customers and meet specific client goals.


Required Skills

  • Develop data models for graph databases.
  • Build ETL pipelines to surface data from various RDBMS systems and create graph databases (e.g. Neo4j, Ongdb) or other graph-based data representations (e.g. GraphFrames, networks, etc.).
  • Optimize graph database design and performance.
  • Effectively communicate and work closely with colleagues and clients to build data science applications.
  • Contribute to the development of reusable intellectual capital and assets, such as: processes, documentation, training material, software/code, templates, etc.
  • Respond promptly to client requests or inquiries.


Required Qualifications

  • Bachelor’s in Economics, Statistics, Mathematics, Computer Science or related field, or equivalent experience.
  • 1-5 years experience, preferred.

Required Experience

  • Sound Experience with Neo4j and Cypher query language.
  • Experience with Spark Graph Frames and Graph X.
  • Sound Experience with SQL Programming.
  • Experience with a statistical software package such as Python or R.
  • Ability to work well in a team environment.
  • Superior problem-solving skills.
  • Excellent communication skills (writing, speaking, and presenting)
  • Ability to work independently, be self-motivated, and be innovative.

Best of Luck!