Data Engineer at Rand Mutual - RMA

Description

THE JOB AT A GLANCE
 
As the Data Engineer, you will be responsible for expanding and optimizing data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. You will also be responsible for supporting software developers, architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. You will also be responsible for supporting the data needs of multiple teams, systems and products.
 
WHAT WILL YOU DO?

Create and maintain data pipeline architecture:

• Assemble large, complex data sets that meet functional / non-functional business requirements
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure ‘big data’ technologies
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics
• Keep our data separated and secure across national boundaries through multiple data centers and Azure regions
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

Stakeholder engagement:

• Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs
• Work with data and analytics experts to strive for greater functionality in data systems.

WHAT YOU'LL BRING TO THE TABLE?

• NQF Level 8: Honours Degree in Computer Science, Informatics, Information Systems or another quantitative field
• Minimum 5 years of experience in a Data Engineer role
• Advanced 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
• 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
• Experience supporting and working with cross-functional teams in a dynamic environment
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra
• Experience with Microsoft Azure cloud services: Data Lake, SQL Data Warehouse, HDInsight
• Experience with stream-processing systems: Spark-Streaming, Azure stream analytics
• Experience with object-oriented/object function scripting languages: Python, C++, C#, etc