About the Role

At Capitec, Data Engineers help build and optimise the pipelines, platforms and data systems that transform complex data into reliable, accessible insights.

Our Data

Engineering environment supports large-scale banking data, connects complex data sources to business needs, and focuses on secure, scalable and future-ready data solutions. We’re building a Data Engineer Talent Community for future opportunities across Data Engineer Levels. This is not for one specific vacancy — it’s a way for talented data engineers to connect with us early, learn about future opportunities, and be considered when roles aligned to your experience become available.You’ll be part of an environment where data engineering is more than maintaining pipelines.

Responsibilities

- Depending on your level of experience, future Data Engineer opportunities may include:
- This is an chance to connect with future roles in a data environment that offers:
- Enterprise-scale impact
- work on data solutions that support banking products, decisions, risk, client experience and operational insight across a large retail banking environment
- A modern technical environment
- grow your skills across Python, SQL, AWS, Redshift, cloud data warehouses, data lakes, CI/CD, Git, Terraform, orchestration, data quality and governance.
- Growth across levels
- progress from foundational engineering delivery to independent pipeline ownership, solution design, platform engineering, technical mentorship and staff-level contribution.
- Purposeful engineering
- build reliable, accessible and future-ready platforms that help turn complex data into insight and innovation.
- Continuous learning
- role information and onboarding material reference learning pathways, AWS Cloud Practitioner Essentials, AWS DevOps Tools,



AWS Glue and Terraform Associate learning topics for Product Data Engineers.
- Designing, building, testing and maintaining ETL/ELT pipelines and data infrastructure that support analytics, reporting, product, risk and client experience decisions.
- Working with cloud-native data platforms, including AWS-focused environments, Redshift or similar cloud data warehouses, data lakes and data warehouses.
- Using Python, SQL, Git, CI/CD, Terraform or other Infrastructure as Code practices to build reliable, scalable and production-grade data solutions.
- Collaborating with Data Architects, Solutions Architects, Analysts, Product teams and technical stakeholders to translate business needs into practical data solutions
- Improving data quality, monitoring, governance, performance, reliability and scalability across the data ecosystem.
- Growing from foundational engineering delivery into independent pipeline ownership, solution design, technical leadership, mentorship and platform-level impact.

Requirements

- Bachelor's Degree in Information Technology
- Expert level SQL knowledge with query optimisation and tuning and indexing strategies. Architecture design for batch and streaming systems
- Deep knowledge of multiple programming languages and implementation of advanced algorithms for data processing.
- Design enterprise wide real-time / batch data integration architectures.
- Advanced knowledge of one cloud platforms data services.
- Design and implementation of data lake,



data warehouse or other patterns. Implementation of enterprise-wide data governance frameworks with automated quality and monitoring.
- Ability to performance optimize across heterogeneous systems.
- Design of multi-environment GitOps strategies, that includes feature flags and other advanced techniques.
- Design & Implementation of containerized data solutions and infrastructure using infrastructure as code
- Design and configuration enterprise workflow orchestration tools and pipelines
- Length of experience required is conditional on the qualifications obtained but must include:
- Proven track record of leading large-scale data engineering projects and driving business impact through data solutions
- Experience with advanced data engineering tools and software (e.g., SQL, Python, Java, Apache Spark, Hadoop).
- Experience with machine learning algorithms and their application in predictive analytics
- Experience in designing and implementing complex data architecture and infrastructure.
- With cloud computing platforms (e.g., AWS, Azure, Google Cloud) and their data services 2.
- Experience in aligning data engineering projects with business strategy and goals.
- Experience in providing data-driven recommendations to senior management and influencing decision-making.
- Experience in leading and mentoring less experienced engineers and data teams.
- In people development, sharing and training.
- Analytical Skills
- Communications Skills
- Computer Literacy (MS Word, MS Excel, MS Outlook)
- Interpersonal & Relationship management Skills
- Problem solving skills
- Clear criminal and credit record

Preferred Qualifications

- Honours Degree in Information Technology - Computer Science or Information Technology

📌 Data Engineer (Ajmer)
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📍 Ajmer