BluNova Jobs 2022 for Data Engineer

We are a JSE-listed company that sells innovative technology for mobile commerce to emerging markets in South Africa and abroad. Our users are rich, poor, urban and rural, and we allow them all to interact and transact on an equal footing. We target many of our services at people who do not have easy access to bank accounts, and we allow them the convenience of being able to transact where and when they want to. At Blue Label Telecoms, we’re looking for outliers. People who have a drive to better themselves, their teams and the business with every decision and interaction. We have built an organisation that recognises achievements and celebrates successes. We thrive on collaboration and offer our team members excellent work environments where enjoyment is a part of the experience.

Job Title: Data Engineer
Location: Sandton, Gauteng, South Africa
Reference #: B156
Contract Type: Temporary

Job Summary:
Responsible for 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

Requirements:
RESPONSIBILITIES:
Data:
Identify shortcomings and suggest improvements to existing processes, systems and procedures, then delivers a plan for a small element of a change management program with guidance from a project/program manager.

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 xxxxxxxxx into an innovative industry leader.
Monitor the existing metrics, analyse data, and lead partnership with other Data and Analytics teams in an effort to identify and implement system and process improvements. Utilise data 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, etc.
Developing ETL processes that convert data into formats for consumption.

Risk, Regulatory, Prudential and Compliance:
Responsible for executing testing and validation in line with data governance and quality business requirements.

People:
Liaise with and collaborate with data analysts, data warehousing engineers, and data scientists in finding and applying best practices within the Data and Analytics department as well as defining the business’s data requirements, which will ensure that the collected data is of a high quality and optimal for use across the department and the business at large.
Acts as a subject matter expert from a data perspective and provides input into all decisions relating to data engineering and the use thereof. Provide guidance in terms of setting governance standards.

BEHAVIORAL COMPETENCIES:
Strategy
Manages Complexity
Ensures Accountability
Collaborates
Plans and Aligns
Tech Savvy

SKILLS:

IT Architecture
Data Integrity
IT Applications
Data Analysis
Knowledge Classification

Computer Skills:
Risk Management
Policy and procedures
Contract Management
Costing and Budgeting
Project Management
Data Collection and Analysis
Compliance Management
Health and Safety
Customer and Market Analysis
Data Control

Important Hard Skills:
Database systems (SQL and NoSQL). Data engineer must know how to manipulate database management systems (DBMS), which is a software application that provides an interface to databases for information storage and retrieval.
Data warehousing solutions.
ETL tools. ETL (Extract, Transfer, Load)
Data APIs. Allows two applications or machines to communicate with each other for a specified task.
Python, Java, R and Scala programming languages.
Understanding the basics of distributed systems.

Important Soft Skills:
Communication skills. Interface with machine learning engineers, data analysts,
CTOs, and developers. They may also work with other teams or business units to gather requirements and define the scope of a project.
Collaboration. Need to understand the expectations of the teams they’re working with, how frequently they need to be updated, and what their pain points are.
Presentation skills. May be expected to perform data analysis and present their findings to stakeholders.

EDUCATION:
Matric
Post Graduate Degree: Information Technology
Post Graduate Degree: Information Studies
Masters Degree: Information Technology
Masters Degree: Information Studies

EXPERIENCE:
IT Architecture: Architectural methodologies used in the design and development of IT systems.
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.
IT Applications: Knowledge and understanding of IT applications and architecture.
Data Analysis: Ability to analyse statistics and other data, interpret and evaluate results, and create reports and presentations for use by others.
Knowledge Classification: The ability to apply metadata to information to make it easy for other people to find.
Apache Spark. (supports programming languages Python, Scala, Java, and R) C++.
Amazon Web Services.
Amazon S3.
Databricks

To Apply:

Click Here!

Application Deadline: 08/06/2022