Analyst, Data at Standard Bank Group

JOB DESCRIPTION

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. Designing and developing scalable ETL packages from the business source systems and the development of ETL routines in order to populate databases from sources and to create aggregates. Oversee large-scale data Hadoop platforms and to support the fast-growing data within the business.

QUALIFICATIONS

Type of Qualification

First Degree: Information Studies/Technology

Experience Required

• 5 years Data & Analytics; Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL 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.
• Technology Business Partnering; 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.
• Information Lifecycle Management -Technical; 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.

ADDITIONAL INFORMATION

Behavioural Competencies

• Adopting Practical Approaches
• Articulating Information
• Challenging Ideas
• Checking Details
• Examining Information

Technical Competencies

• Applications: Microsoft Office Suite
• Data Analysis and Integrity
• Database Administration
• IT Architecture
• Knowledge Classification