Data Analyst will be responsible for support in providing infrastructure, tools and frameworks used to deliver end-to-end solutions to business problems. The successful candidate’s role will also entail building scalable infrastructure for supporting the delivery of business insights from raw data sources with a focus on collecting, managing, analysing, visualizing data and developing analytical solutions.
Key responsibilities
Data
- Assist in creating and maintaining optimal data pipeline architecture and creating databases optimized for performance, implementing schema changes, and maintaining data architecture standards across the required Standard Bank databases
- Work alongside data scientists to help make use of the data they collect
- Assemble large, complex data sets that meet functional / non-functional business requirements and align data architecture with business requirements
- Assist in enabling and running data migrations across different databases and different servers and defines and implements data stores based on system requirements and consumer requirements
- Assist in performing thorough testing and validation in order to support the accuracy of data transformations and data verification used in machine learning models
- 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
- Analyse complex data elements and systems, data flow, dependencies, and relationships in order to contribute to conceptual physical and logical data models
People
- 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
Product
- Utilise data under supervision to discover tasks that can be automated and identify, design, and implement internal process improvements, automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability
- 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
- Manager large-scale data Hadoop platforms and to support the fast-growing data within the business
- Build 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
Minimum Qualifications
- Post Graduate Degree Information Studies
- Post Graduate Degree Information Technology
Experience Required
- Data & Analytics
- Data Monetisation
3-4 years’ Experience with:
- Data tools: Hadoop
- Spark, Kafka
- Experience with Relational SQL and Nosql databases, including Postgres and Cassandra
- Experience with data pipeline and workflow management tools:
- Azkaban, Luigi, Airflow,
- Experience with AWS cloud services:
- EC2, EMR, RDS,
- Experience with stream-processing systems: Storm
- Spark-Streaming
- Experience with object-oriented/object function scripting languages: Python
- Java, C++, Scala
Data Analytics Technical Competencies
- Data Analysis – Ability to analyse statistics and other data, interpret and evaluate results, and create reports and presentations for use by others
- Proficiency Level 3 SEASONED – Applies concepts without requiring supervision, able to provide technical guidance when required
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
- Proficiency Level 3 SEASONED – Applies concepts without requiring supervision, able to provide technical guidance when required
Database Administration
- Refers to the knowledge and experience required to manage the installation, configuration, upgrade, administration, monitoring, and maintenance of physical databases
- Proficiency Level 3 SEASONED – Applies concepts without requiring supervision, able to provide technical guidance when required
IT Applications
- Knowledge and understanding of IT applications and architecture
- Proficiency Level 2 PROFICIENT – Clear knowledge and application of the concept
IT Architecture
- Architectural methodologies used in the design & development of IT systems
- Proficiency Level 2 PROFICIENT – Clear knowledge and application of the concept
Knowledge Classification
- The ability to apply metadata to information to make it easy for other people to find
- Proficiency Level 2 PROFICIENT – Clear knowledge and application of the concept
To apply for this role, email your CV to khanyin@mindworx.co.za
For more information about this role, go to Placement Partner