Data Engineer: BluNova at Blue Label Telecoms

Job Purpose

• 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.

Job 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 data requirements, which will ensure that the collected data is of 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

Requirements

Behavioural Competencies

• Strategy
• Manages Complexity
• Ensures Accountability
• Collaborates
• Plans and Aligns
• Tech Savvy

Education

• Post Graduate Degree: Information Technology
  Post Graduate Degree: Information Studies
  Masters Degree: Information Technology
  Masters Degree: Information Studies

Experience

• IT Architecture
• Data Integrity
• IT Applications
• Data Analysis
• Knowledge Classification
• C++.
• Amazon Web Services.
• Amazon S3.
• Databricks
• Minimum of 3 years’ progressive experience as a Data Engineer

Skills
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
• Collaboration
• Presentation skills