Data Engineer

Industry: Finance
Company size: 11-50

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Job description

An emerging company that aims to eliminate fraud and inefficiency through network validation is looking for a Data Engineer. The selected candidate will analyze business requirements and translate them into logical data models. The company is building an all-in-one platform to help businesses accelerate and protect their customers. This is a nice opportunity for those who want to work with a world-class company that has been setting the industry standards.


Job Responsibilities:

  • Build and maintain the infrastructure to answer queries and enhance processes by working with data to address business problems
  • Aid in streamlining the data science procedures, as well as expanding the customer lifecycle and retention models
  • Develop data models and pipelines for research, reporting, and machine learning in collaboration with the data science and business intelligence teams
  • Be a proponent of best practices and lifelong learning
  • Model front-end and back-end data sources to get a better view of how users move around the system and to perform powerful data analysis
  • Create data pipelines that clean, transform, and combine data from a variety of sources
  • Create and manage an MLOps platform for deploying models that may be used to generate predictions and respond to questions

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 7+ years of relevant experience as a data engineer
  • 5+ years of experience with Python, SQL, and data visualization/exploration tools, architecting complex data workflows
  • Extensive experience working with Kafka and Docker
  • Conversant with the AWS ecosystem, specifically RedShift, Athena, messaging brokers, and RDS
  • Track record of building or maintaining ETL processes
  • Solid proficiency in RESTful APIs, architecting complex systems with batch and real-time workloads, monitoring, and instrumenting production systems
  • Previous expertise in developing and managing engineering teams and cross-functional project delivery schedules
  • Nice to have some knowledge of Amazon Kinesis, AWS DevOps, and Zookeeper
  • Strong written and verbal communication skills

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