Quantexa Data Engineer Job

Who we are

The Group Anti-Fraud Solution aims to support our client's Entities in fighting Fraud. Composed of two Solutions: Tactical Fraud Fighting (in-house built solution) and Strategic Fraud Fighting (Quantexa solution), the product helps to detect suspicious claims based on Predictive Model Scoring engine, Business Rules Scoring Engines, Network Rules Scoring engines as well as Network Investigation. 

What you'll be doing

• Writing defensive, fault tolerant and efficient code for production level data processing systems
• Configuring and deploying Quantexa software using tools such as Spark, Hadoop, Scala, Elasticsearch, with our platform being hosted on clouds, such as Microsoft Azure and AWS
• You’ll be a trusted source of knowledge for your clients. And you’ll articulate technical concepts to a non-technical audience so they can make key decisions
• Collaborate with our solution architects and other engineers to champion solutions and standards for complex big data challenges
• You proactively promote knowledge sharing and ensure best practice is followed. 
• Participate in Scrum ceremonies such as sprint planning, daily stand-ups, sprint reviews, and retrospectives 

What you'll bring along

• Minimum 5-7 years of experience in a similar role
• Strong Quantexa product knowledge (QTX certification) 
• Background in hands-on technical development, with at least three years of industry experience in a data engineering role or equivalent, and preferably at least four years of software industry experience. 
• Proficiency in Scala, java, python, or a programming language associated with data engineering. 
• As an expert in building and deploying production level data processing batch systems, you’ll share an appreciation of what makes a high quality, operationally stable system and how to streamline all areas of development, release, and operations to achieve this. 
• A strong technical communication ability with demonstrable experience of working in rapidly changing client environments. 
• Knowledge of testing libraries of common programming languages (such as ScalaTest or equivalent). Importantly, you’ll know the difference between varying test types (unit test, integration test) and can cite specific examples of what they have written themselves 
• Data Warehouse background is a must, solid knowledge regarding data models, especially in the financial sector 
• Preferred experience with any insurance company 
• Experience with a variety of modern development tooling (e.g. Git, Gradle, Nexus) and technologies supporting automation and DevOps (e.g. Jenkins, Docker and a little bit of good old Bash scripting). You’ll be familiar with developing within a version-controlled process that regularly makes use of these tools and technologies. 
• Strong aptitude and desire to learn new technologies and tools 
• Self-driven with and ability to work closely with business analysts and development team to work towards quality product rollout