Data Analyst - Insurance

Business Segment: Insurance & Asset Management
Location: ZA, undefined, Johannesburg, Ellis Street 4
This role resides within Standard Insurance finance and requires the incumbent to provide infrastructure, tools and frameworks used to deliver end-to-end solutions to Finance IT and data 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.
Qualifications
Minimum Qualifications Type of Qualification: Postgraduate Degree
Field of Study: Information Studies or Information Technology
Experience Required Short term insurance experienceBasic knowledge accountingUnderstanding data mining and data enrichment for financial reportingWorking knowledge of IFRS 17 reporting softwareData Monetisation 5-7 years 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 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.
Information Lifecycle Management - Technical 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.

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