Data Engineer

An established insurance company is seeking to hire a highly skilled and experienced Data Engineer to join their team. Your: Formal Education: * Degree in Data Science, Information Technology, Computer Science or equivalent Advantageous : * Cloud Data Certifications * Exposure to regulated environments,financial services, fintech Experience: * Minimum of 2 years in a data engineer role or a similar technical role. Responsibilities: * Build and maintain ETL pipelines supporting a multi-tenant data platform, ingesting data from APIs, databases, and event sources. * Build and maintain Data Platform APIs that allow teams to ingest, process, and access data easily and reliably. * Implemented tenant-specific logic by following existing configuration and naming conventions. * Apply tenant-level data isolation using schemas, partitions, or access controls * Build models from existing templates used for financial and operational reporting. Develop models for analytics and reporting, maintaining consistency with shared data models. * Monitor scheduled pipelines, investigate failures, and resolve data quality issues and inconsistencies. * Maintain daily and incremental data loads into the data warehouse. * Assist with onboarding new clients by validating source data and testing pipeline outputs. * Work closely with senior data engineers to learn patterns for multi-tenant data isolation. * Collaborate with analytics, product, and customer facing teams to understand reporting needs. * Support strict regulatory and audit requirements by following data handling,retention, and audit guidelines. * Handle financial and sensitive data (PII) according to company policies and regulatory standards (e.g. POPIA) * Apply least-privilege access and rolebased access controls, and support data protection through masking, encryption,and established security standards. Competencies & Skills: Technical Skills: * Programming languages – Good knowledge of programming languages such as Python, especially used for pipeline and data manipulation. * SQL – working experience using SQL for data cleaning, aggregation, data transformation and integration. * Data Warehouse - have a fundamental understanding of data warehousing solutions and platforms. * Databases – hands on experience working with relational and non-relational databases. * Cloud computing – comfortable building data solutions using cloud hosted services or data platforms. Data Engineering Practice: * Analytics skills – strong problem solving skills, understand data characteristics, identify patterns, and data quality issues. * Data modelling and ETL – Is able to communicate and translate business requirements into existing data models. * Data Pipeline Development– build and validate smaller scale data pipelines independently. * CI/CD and Version Control – apply best practice for managing pipelines and data workflows. Compitant Candidates Recruiter