Overview:
The Data Engineer plays a crucial role in the organization by designing developing and maintaining scalable data pipelines to support datadriven initiatives. This role is responsible for ensuring the availability reliability and efficiency of data systems thus enabling the organization to make informed decisions based on highquality data.
Key Responsibilities:
- Work across all aspects of data from engineering to building sophisticated visualizations machine learning models and experiments
- Analyze and interpret large (PBscale) volumes of transactional operational and customer data using proprietary and open source data tools platforms and analytical tool kits
- Translate complex findings into simple visualizations and recommendations for execution by operational teams and executives
- Be part of a fastpaced industry and organization where time to market is critical
Required Qualifications:
- Degree in a quantitative discipline such as Mathematics/Statistics Actuarial Sciences Computer Science Engineering or Life Sciences
- 35 years of fulltime work experience in an Analytics or Data Science role
- A selfdriven team player with the ability to quickly learn and apply new tools and techniques such as proprietary analytical software data models and programming languages
- A natural curiosity to identify investigate and explain trends and patterns in data and an ability to analyse and break down complex concepts and technical findings into clear and simple language for communication
- A passion for Emerging Technologies related to Blockchain Machine Learning and AI.
Competency in two or more of the following:
- An analytical software (e.g. R SAS)
- A data visualization tool (e.g. QlikView Tableau PowerBI)
- A relational or graph database management tool (e.g. SQL NoSQL Neo4J)
- Programming (e.g. VBA C Java Python)
data models,sql,data,data visualization tool,mathematics,machine learning,relational database management tool,ai,data tools,quantitative discipline,data-driven initiatives,engineering,java,emerging technologies,statistics,data engineering,graph database management tool,computer science,tableau,analytical tool kits,blockchain,proprietary analytical software,python,machine learning models,programming languages,programming,analytical software,scalable data pipelines,data science,analytics,visualizations,open source data tools,life sciences,nosql