Associate, Full Stack Data Engineer

at  The Edge Partnership

O
Posted by
Oliver Lim
Recruiter
Our Client is a global financial services group and they are looking to hire a data engineer within their data team. The person would be looking at the firm’s data strategy, driving transformational change through data capabilities, enforce data governance for both transformation benefits and regulatory compliance and enhancing their data culture.
He/She will work with Business and Corporate functions, ensuring that the firm’s data assets are managed in accordance with the firm’s data management framework, policies, and standards.

Job Responsibilities and Requirements:

• Develop data architecture and deliver data-analytics platforms and solutions across on-premises, cloud, and hybrid environments.
• Provide expertise in information delivery and analytics, including data preparation, data insights, and visualization using BI tools, as well as advanced data prediction using AI, ML, DL, etc.
• Oversee AI/ML Ops, including the integration, deployment, and monitoring of AI/ML products and solutions.
• Demonstrate expertise in data management to ensure analytics products are appropriate, ethical, and well-controlled.
• Act as a trusted partner by shaping the information and analytics agenda and collaborating with all the firm’s businesses to develop their information and analytics adoption roadmaps.
• Design and develop scalable data pipelines to collect and process large volumes of data from multiple sources.
• Build physical data models and ETL processes to ensure data quality, integrity, and accessibility.
• Develop and maintain highly scalable and fault-tolerant microservices, including efficient server-side APIs.
• Experience with CI/CD, Jenkins, Ansible, DevOps processes, and enterprise integration patterns.
• Proficiency in programming languages (Python, Java, etc.) and orchestration tools like Airflow.
• Experience with cloud technologies such as EC2, EMR, Snowflake, or similar tools, with the ability to drive design and data model discussions and hybrid data architecture.
• Proficiency in REST services, JSON data, Python 3, and Linux/Unix Shell Scripting.
• Expertise in modern data management methodologies and architecture, such as building data products and implementing data mesh.
• Experience with machine learning libraries and frameworks like LangChain, TruLens, MLFlow, TensorFlow, Scikit-learn, or PyTorch.
• Deploy machine learning models into production environments and monitor their performance over time.
• Collect, clean, and analyse large datasets to train and evaluate machine learning models.
• Flexibility to adapt to multiple demands, shifting priorities, ambiguity, and rapid change.
• Experience with senior stakeholder management is an added advantage.
• Excellent communication (verbal, written, listening), presentation, and interpersonal skills.

Education and Experience:

• Degree or Master’s in quantitative fields (Computer Science, Statistics, or similar).
• Minimum of 5 years of relevant data experience in data engineering/MLOps, full stack engineering, preferably in financial organizations.
• Experience working with multi-cultural, multi-disciplined, globally dispersed teams.
• Certifications in relevant technologies or frameworks are a plus.

Please contact Oliver Lim or email your cv directly in word format to oliver@theedgepartnership.com
Please note that due to the high number of applications only shortlisted candidates will be contacted. We regret to inform you that your application for this position was unsuccessful if you do not hear from us in the next 5 business days.
EA Licence: 16S8131
Recruiter Licence: R1657051
Job ID JOB-13273

• Develop data architecture and deliver data-analytics platforms and solutions across on-premises, cloud, and hybrid environments.
• Provide expertise in information delivery and analytics, including data preparation, data insights, and visualization using BI tools, as well as advanced data prediction using AI, ML, DL, etc.
• Oversee AI/ML Ops, including the integration, deployment, and monitoring of AI/ML products and solutions.
• Demonstrate expertise in data management to ensure analytics products are appropriate, ethical, and well-controlled.
• Act as a trusted partner by shaping the information and analytics agenda and collaborating with all the firm’s businesses to develop their information and analytics adoption roadmaps.
• Design and develop scalable data pipelines to collect and process large volumes of data from multiple sources.
• Build physical data models and ETL processes to ensure data quality, integrity, and accessibility.
• Develop and maintain highly scalable and fault-tolerant microservices, including efficient server-side APIs.
• Experience with CI/CD, Jenkins, Ansible, DevOps processes, and enterprise integration patterns.
• Proficiency in programming languages (Python, Java, etc.) and orchestration tools like Airflow.
• Experience with cloud technologies such as EC2, EMR, Snowflake, or similar tools, with the ability to drive design and data model discussions and hybrid data architecture.
• Proficiency in REST services, JSON data, Python 3, and Linux/Unix Shell Scripting.
• Expertise in modern data management methodologies and architecture, such as building data products and implementing data mesh.
• Experience with machine learning libraries and frameworks like LangChain, TruLens, MLFlow, TensorFlow, Scikit-learn, or PyTorch.
• Deploy machine learning models into production environments and monitor their performance over time.
• Collect, clean, and analyse large datasets to train and evaluate machine learning models.
• Flexibility to adapt to multiple demands, shifting priorities, ambiguity, and rapid change.
• Experience with senior stakeholder management is an added advantage.
• Excellent communication (verbal, written, listening), presentation, and interpersonal skills