Senior Data Engineer

Primary Purpose: A specialized skill is required to effectively manage and develop data and analytics capabilities that provide insight and aid quick decision making.

A Data Engineer will extract and acquire data from different sources and apply algorithms to provide insight to different departments.

Minimum Requirements:

1. Qualifications:

• Degree or Diploma in computer science, mathematics, statistics, Engineering, or related field
• Microsoft Certification Advantageous
• Strong math and analytical skills are essential to complete job requirements successfully
• Able to compile and organize statistical information and present findings to management
• Knowledge of systems development, including system development life cycle, design and testing techniques
• Project management approaches and requirements
• Proficiency in data modelling and design

Experience:

1. A minimum of 4-7 years working experience in a technology environment
2. Experience working with private and sensitive personal information

Competencies:

1. Technical:

• Expert in Microsoft BI stack SQL (SSIS, SSAS, SSRS, T-SQL)
• Knowledge of programming languages (e.g., Python)
• Data warehousing skills
• Experience working with Power BI
• Experience working on large and complex datasets
• Understanding of cutting-edge cloud technology and framework to enable data science
• Understanding meta-data management
• Knowledge of algorithms and data structures

• Act with conviction and courage
• Results Driven
• Positive Disposition
• Nimble Learning
• Embrace Change
• Think and Act Strategically
• Advocate the Vision and Purpose
• Data Mindedness
• Lead, Develop and Motivate Self and Others
• Collaborate to make Bidvest Bank better

Duties and Responsibilities:

1. CUSTOMER CENTRICITY:

• Increase customer satisfaction
• Incorporate customer suggestions into future products and experience developments
• Regular Feedback and Communication with Customers
• Understanding customer requirements

• Design and develop data warehousing solutions
• Identifying, designing, and implementing internal processes
• Preparing data for predictive and prescriptive modeling
• Improving data quality and efficiency
• Integrating technical functionality, ensuring data accessibility, accuracy, and security
• Identifying data sources, both internal and external, and working out a plan for data management that is aligned with organizational data strategy
• Create dashboards and reports using visualization tools
• Working with stakeholders including data, design, product and assisting them with data-related technical issues and requirements
• Build data solutions that leverage controls to ensure privacy, security, compliance and data quality
• Collaborate with teams within the bank to enable delivery of data and advanced analytics system capability
• Participate in code reviews
• Monitor models for post-production

• Measure, monitor and control the impact of poor quality data
• Proactively identify areas of specialization related problems, determine cause and effect and recommend best solution to resolve the problem
• Improving data quality and efficiency
• Creation of new data validation processes
• Comprehensively test solutions to ensure delivery according to identified requirements
• Research and rigorously evaluate sources of information to determine possible limitations in reliability or usability
• Apply sampling techniques to effectively determine and define ideal categories to be questioned
• Define and utilize statistical methods to solve industry-specific problems in varying fields, such as economics and engineering
• Understand the integration of various systems and processes to apply practically in the area of work
• Reduce the ratio of data errors and the data time to value

• Include customers in the ideation process
• Translate business requirements and functional requirements into technical specifications

• Data accuracy, availability, security, and accessibility in the data management system
• Compare and analyze provided statistical information to identify patterns, relationships, and problems
• Preparing data for predictive and prescriptive modeling

• Empower teams through training and knowledge sharing
• Train and assist other members of the team on how to meticulously organize findings and read data collected

This position is advertised in line with our commitment to Employment Equity.