Manager, Data Management

Overview

Business Segment:
Personal & Private Banking

Location:

ZA, GP, Johannesburg, 30 Baker Street

Provide infrastructure, tools and frameworks used to deliver end-to-end solutions to business problems. Build scalable infrastructure for supporting the delivery of clear business insights from raw data sources; with a focus on collecting, managing, analysing, visualising data and developing analytical solutions. Responsible for expanding and optimising Standard Bank's data and data pipeline architecture, whilst optimising data flow and collection to ultimately support data initiatives.

• Provide infrastructure, tools and frameworks used to deliver end-to-end solutions to business problems.
• Build scalable infrastructure for supporting the delivery of clear business insights from raw data sources; with a focus on collecting, managing, analysing, visualising data and developing analytical solutions.
• Responsible for expanding and optimising Standard Bank's data and data pipeline architecture, whilst optimising data flow and collection to ultimately support data initiatives.

• Type of
  
  Qualification:
  
  First Degree
• Field of Study: Information Studies
• Type of
  
  Qualification:
  
  First Degree
• Field of Study: Information Technology
• Experience Required
• Data Monetisation
• Data & Analytics
• 5-7 years
• Experience with big data tools:
  Hadoop, Spark, Kafka, etc.
  
  Experience with relational SQL and No
  
  SQL databases, including Postgres and Cassandra. Experience with data pipeline and workflow management tools:
  Azkaban, Luigi, Airflow, etc. Experience with AWS cloud services: EC2, EMR, RDS, Redshift. Experience with stream-processing systems:
  Storm, Spark-Streaming, etc. Experience with object-oriented/object function scripting languages:
  Python, Java, C++, Scala, etc.
• 5-7 years
• Strong analytic skills related to working with unstructured datasets. Build processes supporting data transformation, data structures, metadata, dependency and workload management. A successful history of manipulating, processing and extracting value from large disconnected datasets. Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores.
• 5-7 years
• Working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. Experience building and optimizing 'big data' data pipelines, architectures and data sets. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.