Product Data Engineer I

Join Us in Becoming the Best Bank in the World!!

We appoint energized and motivated people for their potential and continuously look for talented, driven individuals to help us innovate and evolve. That is why we focus on finding the right people for the right jobs. We love what we do because we focus on making a positive difference for our clients and employees.  Our company DNA is built around talented and committed teams dedicated to build a brand that we are proud of and earns the trust of our clients.

Who We Are

We are a bank, but we’re much more than that. We believe that banking is about enabling people to control their financial lives through banking that is simplified, accessible, affordable and delivered through personal experience. By helping our clients manage their financial lives better, we enable them to live better. 

Why Choose Us

At Capitec, we offer our best by living up to our CEO values in every situation – we always put the Client first, act with Energy and take Ownership. And to support people in being their best, our Employee Value Proposition offers every value to all team members through cohesive teams, growth opportunities as well as employee benefits and savings. We make it a priority to ensure that each member of the Capitec team feels welcome, valued, focused, and has the opportunity to grow. 

About the role:

• To maintain, enhance and develop new Enterprise tables in the Enterprise Data Warehouse based on the Kimball methodology
• Contribute to evolving the Capitec data landscape through the sharing of knowledge, contributing new data features, end enhancing/streamlining existing data products, e.g. improve and optimise the code

Education (Minimum)

Education (Ideal or Preferred)

Knowledge and Experience

Experience:
 

Minimum:

• At least 1 years proven engineering experience in warehouse environments, preferred in AWS Redshift SQL

OR

• At least 1 years of dimensional data modelling experience or 1 year of engineering experience.

• Proven experience in:

• SQL, Control M (Scheduling toolset)

• Version control in Git and the use of CI/CD deployments

Ideal:

• Use of dimensional data structures (Kimball)

• Core AWS services (S3, Redshift, Airflow,

• Columnar database management systems

• Data warehouse architectures

• AWS Well-Architected Framework

• Solid understanding of Banking business model and systems environment

• Use of dimensional data structures (Kimball)

• Software version control systems (git) and deployment tools (CI/CD)

• Collaboration tools (JIRA, Confluence, Draw.io)

• Trusted insight into Data Governance, Data Quality, Metadata, Lineage and Data Security

Knowledge:

Minimum:

Must have a detailed knowledge of:

• SQL knowledge
• Data analysis
• Software testing knowledge

Ideal:

• Data analysis and design

• Data architecture (technical design and implementation processes)

• DPLC

Skills

Additional Information