Data Engineer/ML
India
Applications have closed
Tookitaki
Make your financial crime compliance programme effective and sustainable with our award-winning FinCense suite of solutions. Request a demo today.Location: India,None,None
Data Engineer
Experience-1+ yrs
Summary:
You have a passion for building big data solutions that solve real-world problems.
Example Activities:
- Build a Big Data processing and feature engineering framework for transaction monitoring
- Design and build real-time pipelines for AML product
- Implementing a scalable graph analysis framework
Your Responsibilities:
- Take full ownership in designing and implementing big data pipelines (both batch and real-time) to support the product needs
- Work closely with data scientists, engineers and product managers to deliver the end-to-end product
- Optimize the current production big data pipelines
- Perform best practices in design, development and documentation
About you:
You should have relevant experience to the role, as:
- Strong programming skills
- Building robust and scalable data infrastructure (both batch and real-time processing) to support the needs of internal and external users
- Experience in building big data pipelines for machine learning products
- Strong understanding of data modeling
- Experience with graph databases is a plus
- Experience with building cloud-based or on-premise big data and machine learning platform services is a plus
More generally, we expect you to have the quality of the following:
- Take strong ownership of your work and are driven to deliver the product end-to-end
- Excited about making an impact in building excellent products and have a strong curiosity
- Collaborate with the product team and other stakeholders to build the right thing that can generate the most impact for our customers
- Hold high standards and pursue excellence
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Big Data Data pipelines Engineering Feature engineering Machine Learning Pipelines
Perks/benefits: Team events
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