Location: ZA, GP, Johannesburg, Baker Street 30Support in providing infrastructure, tools and frameworks used to deliver end-to-end solutions to business problems. Build scalable infrastructure for supporting the delivery of business insights from raw data sources with a focus on collecting, managing, analysing, visualising data and developing analytical solutions. Responsible for expanding and optimising the organisations data and data pipeline architecture, whilst optimising data flow and collection to ultimately support data initiatives.ResponsibilitiesBuild analytics tools that utilise the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. Create data tools for analytics and data scientist team members that assist them in building and optimising Standard Bank into an innovative industry leader.Perform ad-hoc analyses of data stored in Standard Banks databases and writes SQL scripts, stored procedures, functions, and views. Proactively analyses and evaluates the Standard Banks databases in order to identify and recommend improvements and optimisation. Deploy sophisticated analytics programs, machine learning and statistical methods.Liaise and collaborate with the entire EDO team, providing support to the entire department for its data centric needs. Collaborate with subject matter experts to select the relevant sources of information and translates the business requirements into data mining/science outcomes. Presents findings and observations to team for development of recommendations.QualificationsDegree - Information Technology/Information Studies (Min)Post Graduate Degree - Information Technology/Information Studies (Pref)Experience Required3 - 4 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.3 - 4 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.3 - 4 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.CompetenciesInterpreting Data: This competency is about interpreting data accurately with an emphasis on the processing and interpretation of numbers. This competency also includes the utilisation of technology.Meeting Timescales: This competency involves individuals adhering to time scales and meeting deadlines. The focus is therefore on being reliable at completing tasks and being punctual.Producing Output: This competency is about ensuring that tasks are completed within the given time-frame. Behaviours that are emphasised in this competency include working at a fast pace, maintaining productivity and multi-tasking.IT Applications: The knowledge and understanding of all relevant IT applications and architecture in order to perform required development and maintenance.Knowledge Classification: The ability to apply metadata to information to make it easy for other people to find.Data Analysis: The ability to analyse statistics and other data, interpret and evaluate results, and create reports and presentations for use by others.
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