Manager, Data Analytics

Company Description

Standard Bank Group is a leading Africa-focused financial services group, and an innovative player on the global stage, that offers a variety of career-enhancing opportunities – plus the chance to work alongside some of the sector’s most talented, motivated professionals. Our clients range from individuals, to businesses of all sizes, high net worth families and large multinational corporates and institutions. We’re passionate about creating growth in Africa. Bringing true, meaningful value to our clients and the communities we serve and creating a real sense of purpose for you.

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.

Qualifications

Minimum Qualifications, certifications or professional memberships

Post Graduate Degree - Information Studies/Information Technology (Pref)

Degree - Information Studies/Information Technology (Min)

Additional Information

Experience Required

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.

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.

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.

Behavioral & Technical Competencies

Adopting Practical Approaches: Adopting practical solutions with an emphasis on learning by doing. This competency requires individuals to utilise common sense when required. Ultimately, this competency is important in order to ensure that organisations implement feasible solutions.

Articulating Information: This competency is about effectively expressing ideas and concerns, giving presentations, explaining things to others as well as showing confidence in the interaction with other people, both strangers and acquaintances alike.

Challenging Ideas: This competency is about an individual facilitating or catalysing change in an organisation. Challenging Ideas emphasises individual behaviours associated with questioning assumptions, challenging established views and arguing personal perspectives.

Checking Details: This competency is concerned with the careful checking and confirmation of details in a task. Another behaviour associated with the Checking Details competency is being accurate. Being accurate requires individuals to have a strong quality orientation as well as to be thorough and detailed in their approach when completing tasks in order to avoid making mistakes.

Data Analysis: Ability to analyse statistics and other data, interpret and evaluate results, and create reports and presentations for use by others.

Data Integrity: The ability to ensure the accuracy and consistency of data for the duration that the data is stored as well as preventing unintentional alterations or loss of data.

Database Administration: Refers to the knowledge and experience required to manage the installation, configuration, upgrade, administration, monitoring and maintenance of physical databases.