Data Analyst III

Job purpose description

 Responsible for overseeing junior data engineering activities and aiding in

building the organisations data collection systems and processing pipelines.

Oversee infrastructure, tools and frameworks used to support the delivery

of end-to-end solutions to business problems through high performing data

infrastructure.

Responsible for expanding and optimising the organisations data and data

pipeline architecture, whilst optimising data flow and collection to

ultimately support data initiatives.

Qualifications

Minimum qualification 1 Type of qualification: Post Graduate Degree

Field of study: Information Technology

Minimum qualification 2 Type of qualification: Post Graduate Degree

Field of study: Information Studies

Other minimum qualifications,

certifications or professional

memberships

NA

2

Preferred qualification 1 Type of qualification: Masters Degree

Field of study: Information Technology

Preferred qualification 2 Type of qualification: Masters Degree

Field of study: Information Studies

Other preferred qualifications,

certifications or professional

memberships

NA

Experience

Experience required 1 Job Function: Technology

Job Family: Data Monetisation

Years: 8-10 years

Experience Description: 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[1]oriented/object function scripting languages: Python, Java, C++, Scala, etc.

Experience required 2 Job Function: Technology

Job Family: Data Monetisation

Years: 8-10 years

Experience Description:

Experience required 3 Job Function: Technology

Job Family: Data Monetisation

Years: 8-10 years

Experience Description: 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.

Total number of years

experience

8 years

Additional Job Dimensions

Number of direct reports Number: 1-3

Number of indirect reports Number: 1-10

Financial accountability Type of Budget: Project Budget

Size of Budget (ZAR equivalent): 500 000 - 2,5 million

Type of accountability: Contributes to budget management

Internal relationships Nature of relationship: Provide a service to them

Description or examples: Provide Data engineering guidance, information

services and ensure an effective data engineering capability, works closely

3

with data analysts and data scientists to ensure and effective data team.

Collaborate with technology and project teams.

External relationships Role type of external contact: Vendors

Description or examples: Manage SLA's and technical service delivery of

vendors in the development, implementation and customer service

requirements for all Data Engineering requirements.

Nature of relationship: Manage the relationship

Work environment Physical Requirements 1: No specific physical requirements

Physical Requirements 2: Open plan office

Working Conditions 1: Africa Region travel may be required

Working Conditions 2: Domestic/local travel may be required

Regulatory Requirements

Regulated Role No

Regulations that apply None

Outputs

Data Owns and extends the business's data pipeline through the collection,

storage, processing, and transformation of large data-sets and oversee the

process for creating and maintaining optimal data pipeline architecture

and creating databases optimized for performance, implementing schema

changes, and maintaining data architecture standards across the required  databases.

Data Oversee the assembly of large, complex data sets that meet functional /

non-functional business requirements and align data architecture with

business requirements.

Product 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

into an innovative industry leader.

Product Monitor the existing metrics, analyse data, and lead partnership with other

Data and Analytics teams in an effort to identify and implement system