Data Analytics Consultant

Must have: Scala, Spark, Azure databricks, Kubernetes

Note: Quantexa certification is a Must.

Good to have: Python, Pyspark, Elastic, Restful APIs

ROLE PURPOSE

The purpose of the Data Engineer is to design, build and unit test data pipelines and jobs for Projects and Programmes on Azure Platform. This role is purposed for Quantexa Fraud platform programme, Quantexa certified engineer is a preferred.

KEY ACCOUNTABILITIES

• Analyse business requirements and support and maintain Quantexa platform.
• Build and deploy new/changes to data mappings, sessions, and workflows in Azure Cloud Platform – key focus area would be Quantexa platform on Azure.
• Develop both batch (using Azure Databricks) and real time (Kafka and Kubernetes) pipelines and jobs to extract, transform and load data to platform.
• Perform ETL routines performance tuning, troubleshooting, support, and capacity estimation.
• Conduct thorough testing of ETL code changes to ensure quality deliverables
• Provide day-to-day support and mentoring to end users who are interacting with the data
• Profile and understand large amounts of source data available, including structured and semi-structured/web activity data
• Analyse defects and provide fixes
• Provide release notes for deployments
• Support Release activities
• Problem solving attitude

Keep up to date with new skills - Develop technology skills in other areas of Platform

FUNCTIONAL / TECHNICAL SKILLS

Skills and Experience:

• Exposure to Fraud, financial crime, customer insights or compliance-based projects that utilize detection and prediction models
• Experienced in ETL tools like databricks (Spark) and data projects
• Experience with Kubernetes to deliver real time data ingestion and transformation using scala.
• Scala knowledge would be highly desirable, Python knowledge is a plus
• Strong knowledge of SQL
• Strong Analytical skills
• Azure DevOps knowledge
• Experience with local IDE, design documentations, Unit testing.