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

Qualifications:

1. Degree or Diploma in computer science, mathematics, statistics, engineering, or related field
2. Microsoft Certification Advantageous
3. Strong math and analytical skills are essential to complete job requirements successfully
4. Able to compile and organize statistical information and present findings to management
5. Knowledge of systems development, including system development life cycle, design and testing techniques
6. Project management approaches and requirements Knowledge
7. 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)
2. Knowledge of programming languages (e.g., Python)
3. Data warehousing skills
4. Experience working with Power BI
5. Experience working on large and complex datasets
6. Understanding of cutting-edge cloud technology and framework to enable data science
7. Understanding meta-data management
8. Knowledge of algorithms and data structures

Behavioural:

1. BUSINESS SUCCESS - Act with conviction and courage
2. Results Driven
3. Positive Disposition
4. Nimble Learning
5. BUILDING THE FUTURE - Embrace Change
6. Think and Act Strategically
7. Advocate the Vision and Purpose
8. Data Mindedness
9. WORKING WITH PEOPLE / COLLABORATION - Lead, Develop and Motivate Self and Others
10. Collaborate to make Bidvest Bank better

Duties and Responsibilities

CUSTOMER CENTRICITY: Increase customer satisfaction and incorporate customer suggestions into future products and experience developments.

Regular Feedback and Communication with Customers Understanding customer requirement.

OPERATIONAL EXCELLENCE: Design and develop data warehousing solutions, identifying, designing, and implementing internal processes, preparing data for predictive and prescriptive modeling, creation of new data validation processes and analytical tools, build and deploy scalable models, improving data quality and efficiency, integrating technical functionality, ensuring data accessibility, accuracy, and security.

Maintain data pipelines and databases, coordinating and collaborating with cross-functional teams, stakeholders, and vendors for the smooth functioning of the enterprise data system. Identify data sources, both internal and external, and work 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 and monitor models for post-production.

DATA MANAGEMENT: Measure, monitor, and control the impact of poor quality data. Proactively identify areas of specialization related problems, determine cause and effect, and recommend best solutions to resolve the problem.

Improving data quality and efficiency, creation of new data validation processes, and 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.

Reduce the ratio of data errors and the data time to value.

STAKEHOLDER MANAGEMENT: Include customers in the ideation process, translate business requirements and functional requirements into technical specifications.

Understanding customer requirements and collaborating with stakeholders including data, design, product, and assisting them with data-related technical issues and requirements.

REPORTING: Ensure 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.

LEARNING AND GROWTH: 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.