Requirement for Big Data Analyst

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Senior Associate, Big Data Analyst, Consumer Banking & Core Engine

Business Function

Group Technology and Operations (T&O) enables and empowers the bank with an efficient, nimble and resilient infrastructure through a strategic focus on productivity, quality & control, technology, people capability and innovation. In Group T&O, we manage the majority of the Banks operational processes and inspire to delight our business partners through our multiple banking delivery channels.

Roles & Responsibilities
• The lead data analyst will provide big data analytics support to the Analytics Centre of Excellence
• This role primarily covers partnering with the business and project leader to discover, analyse, process, and visualize the data to develop analytic solutions and support data science needs.
• The role requires to be hands on, guiding and mentoring a team of analysts
• Assemble large, complex data sets that meet functional / non-functional business requirements
• Work with data consumers to enhance the analytic data infrastructure and develop data marts and feature marts to serve different analytics needs
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using big data technologies
• Perform data wrangling and feature engineering to support machine learning
• Create helper functions to automate frequently encountered wrangling and feature engineering tasks
• Execute queries on databases and resolve intricate questions in order to respond to the needs of stakeholders
• Problem-solve computational and analytic challenges by investigating the data, understanding the root questions, and coming up with alternative measurement strategies
• Write codes that are production-ready and reusable
• Develop dashboards and other analytic capabilities to enable stakeholders make the right decisions at the right time

Requirements
• Bachelors/Masters in areas of data analytics or related fields
• At least 10 years of industry experience in data analytics working in a big data environment
• At least 3 years working experience in banking industry with business domain knowledge in retail banking
• Highly proficient and extensive experience with data wrangling, transformation, data analysis, data validation and feature engineering using programming language such as Spark and Python. Excellent knowledge of SQL
• Extensive experience on distributed compute frameworks like Apache Spark and Hadoop, including deployment and optimization activities
• Proficient in using other big data technology, i.e., Cloudera Data Science Workbench, Airflow, Presto, Superset, Alluxio, S3, Confluence, JIRA and Bitbucket or their equivalents
• Expertise in visualization using Qlikview, Tableau and Superset; with certifications
• Experience in publishing and managing content, jobs, and permissions on visualization servers
• Proven ability to balance competing priorities, workloads, and tight timelines in a fast-paced, dynamic work environment
• Ability to communicate technical information to both technical and non-technical stakeholders