RCE-Risk Data Engineer

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RCE-Risk Data Engineer-Leads

Job Description: -

Our Technology team builds innovative digital solutions rapidly and at scale to deliver the next generation of Financial and Non- Financial services across the globe.

The Position is a senior technical, hands-on delivery role, requiring the knowledge of data engineering, cloud infrastructure and platform engineering, platform operations and production support using ground-breaking cloud and big data technologies.

The ideal candidate with 3-6 years of experience, will possess strong technical skills, an eagerness to learn, a keen interest on 3 keys pillars that our team support i.e. Financial Crime, Financial Risk and Compliance technology transformation, the ability to work collaboratively in fast-paced environment, and an aptitude for picking up new tools and techniques on the job, building on existing skillsets as a foundation.

In this role you will:

• Develop a thorough understanding of the data science lifecycle, including data exploration, preprocessing, modelling, validation, and deployment
• Design, build, and maintain tree-based predictive models, such as decision trees, random forests, and gradient-boosted trees, with a low-level understanding of their algorithms and functioning.
• Ingestion and provisioning of raw datasets, enriched tables, and/or curated, re-usable data assets to enable variety of use cases.
• Evaluate modern technologies, frameworks, and tools in the data engineering space to drive innovation and improve data processing capabilities.
  
  

Core/Must Have Skills.

• Significant data analysis experience using python, SQL and spark. Experience in python or spark to write scripts for data transformation, integration and automation tasks.
• 3-6 years’ experience with cloud ML (AWS) or any similar tools.
• Design, build, and maintain tree-based predictive models, such as decision trees, random forests, and gradient-boosted trees, with a low-level understanding of their algorithms and functioning.
• Strong Experience with statistical analytical techniques, data mining and predictive models.
• Conduct A/B testing and other model validation techniques to ensure the accuracy and reliability of data models..
• Experience with optimization modelling, machine learning, forecasting and/or natural language processing.
• Hands-on experience with Amazon S3 data storage, data lifecycle policies, and integration with other AWS services.
• Maintain, optimize, and scale AWS Redshift clusters to ensure efficient data storage, retrieval, and query performance
• Utilize Amazon S3 to store raw data, manage large datasets, and integrate with other AWS services to ensure secure, scalable, and cost-effective data solutions.
• Experience in implementing CI/CD Pipelines in AWS.
• At least 4+ years of experience in Database Design and Dimension modelling using SQL
• Advanced working SQL Knowledge and experience working with relational and NoSQL databases as well as working familiarity with a variety of databases (SQL Server, Neo4J)
• Strong analytical and critical thinking skills, with ability to identify and resolve issues in data pipelines and systems.
• Strong communication skills to effectively collaborate with team members and present findings to stakeholders.
• Collaborate with cross-functional teams to ensure successful implementation of solutions.
• Experience with OLAP, OLTP databases, and data structuring/modelling with understanding of key data points.
  
  

Good to have:

• Apply domain knowledge (if applicable) in financial fraud to enhance predictive modelling and anomaly detection capabilities.
• Knowledge of AWS IAM for managing secure access to data resources.
• Familiarity with DevOps practices and automation tools like Terraform or CloudFormation.
• Experience with data visualization tools like Quick Sight or integrating Redshift data with BI tools (Tableau, PowerBI, etc.).
• AWS certifications such as AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect are a plus.
  
  

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