Join a growing FinTech company that is helping drive the latest initiatives within authentication and due diligence. Be part of a growth business and one of the early leaders in Data Engineering to help guide the team and drive it to new grounds.

Responsibilities

• Work with structured and unstructured data from various sources across multiple ecosystems
• Be able to handle Big Data volumes and create systems to help ingest this volume of data
• Extract data sets with industry schemas to large unstructured and aggregated data sets
• Help design and architect ways to implement data pipelines on cloud native platforms that work at scale
• Take ownership of your end-to-end pipeline and automation of data process
• Design data models that help with transformation, analysis, reports and even data science modelling
• Be able to work with a strong team across multiple functions, including software engineers and data scientists

Requirements

• Holding a Masters or PhD in Analytics, Computer Science or related fields
• Having 5+ years of work in Big Data Engineering tools such as Spark, Hadoop, Hive, Flink etc.
• Proficient in Python and modern relational and NoSQL databases
• Experience with distributed systems and cloud architecture through the likes of AWS or Azure
• Experience with streaming processes
• Able to work on data modelling and ideally building predictive models for data science teams
• Confident in R or MatLab analytical tools with statistical modelling packages for data manipulation
• Experience with data science tools (e.g. Dataiku, Jupyter) is a great plus
• Great if one has docker or linux shell experience

Reaching out