ML Data Engineer

Role : ML Data Engineer

• To work closely with various stakeholders to collect, clean, model and visualise datasets.
• To create data driven insights by researching, designing and implementing ML models to deliver insights and implement action-oriented solutions to complex business problems
• To drive ground-breaking ML technology within the Modelling and Data Science team.
• To extract hidden value insights and enrich accuracy of the datasets.
• To leverage technology and automate workflows creating modernized operational processes aligning with the team strategy.
• To understand, implement, manage, and maintain analytical solutions & techniques independently.
• To collaborate and coordinate with Data, content and modelling teams and provide analytical assistance of various commodity datasets
• To drive and maintain high quality processes and delivering projects in collaborative Agile team environments.

Requirements:

• 7+ years of programming experience particularly in Python
• 4+ years of experience working with SQL or NoSQL databases.
• 1+ years of experience working with Pyspark.
• University degree in Computer Science, Engineering, Mathematics, or related disciplines.
• Strong understanding of big data technologies such as Hadoop, and Messaging systems
• Demonstrated ability to design and implement end-to-end scalable and performant data pipelines.
• Experience with workflow management platforms like Airflow.
• Strong analytical and problem-solving skills.
• Ability to collaborate and communicate effectively with both technical and non-technical stakeholders. • Experience building solutions and working in the Agile working environment
• Experience working with git or other source control tools
• Strong understanding of

  Object-Oriented Programming (OOP)

  principles and design patterns.
• Knowledge of

  clean code practices

  and the ability to write well-documented, modular, and reusable code.
• Strong focus on

  performance optimization

  and writing efficient, scalable code.

Nice to have:

• Experience working with Oil, gas and energy markets
• Experience working with BI Visualization applications (e.g. Tableau, Power BI)
• Understanding of cloud-based services, preferably AWS
• Experience working with Unified analytics platforms like Databricks
• Experience with deep learning and related toolkits: Tensorflow, PyTorch, Keras, etc.