About the Role We are seeking a highly experienced Senior Enterprise Data Engineer to join our enterprise data leadership team. This strategic, senior‑level position is responsible for defining, designing, and governing the long‑term vision of our enterprise data platforms. You will bridge high‑level architectural strategy with hands‑on technical oversight, owning the enterprise data roadmap while ensuring platforms are scalable, secure, and aligned with business objectives. This role requires a technical authority who can influence technology decisions, enforce governance standards, and provide leadership across multiple engineering teams in highly regulated environments. Key Responsibilities Architecture & Strategy Design and own the roadmap for enterprise‑scale data architectures, including data lakes, data warehouses, and virtualization layers. Define and enforce enterprise‑wide standards for data integration, replication, data modeling, and data virtualization. Lead evaluation and adoption of new data technologies, balancing innovation, stability, scalability, and total cost of ownership. Design architectures suitable for analytics, AI, operational reporting, and real‑time use cases. Partner with executives and data leaders to influence long‑term data strategy and investment roadmaps. Implementation & Platform Oversight Lead the architecture and enterprise‑wide implementation of Denodo to create a unified, real‑time data access and virtualization layer. Oversee complex data pipelines built using Qlik Talend (Cloud and On‑Prem) ensuring alignment with enterprise architectural standards. Manage log‑based CDC, real‑time streaming, and heterogeneous database replication using Qlik Replicate. Implement AI‑driven workflow automation using IBM WatsonX Orchestrate to streamline data provisioning and operational processes. Ensure high availability, performance optimization, disaster recovery readiness, and resilience across all critical data services. Provide oversight on SQL optimization and advanced enterprise data modeling approaches (Data Vault 2.0, Anchor Modeling). Governance, Security & Compliance Implement and govern enterprise data governance frameworks, including data lineage, metadata management, and data quality controls. Ensure governance is embedded within the data virtualization layer. Enforce enterprise security standards including RBAC, data masking, encryption, and secure data access. Ensure compliance with regulatory frameworks such as GDPR, HIPAA, SOX, and other industry‑specific requirements. Support Master Data Management (MDM) strategies and enterprise data stewardship initiatives. Leadership & Mentorship Act as a subject matter expert and trusted advisor to data engineers, analysts, architects, and business stakeholders. Mentor senior and junior engineers, promoting technical excellence and continuous improvement. Drive architectural best practices across teams and foster a culture of governance, quality, and innovation. Requirements & Qualifications Must‑Have Skills & Experience 8+ years of progressive experience in data engineering, data architecture, or enterprise data platform roles. 2–3+ years in a leadership or strategic oversight capacity. Expert‑level experience architecting and deploying enterprise data virtualization solutions using Denodo (including Denodo Platform and Data Catalog). Deep expertise in Qlik Talend (Cloud and On‑Prem) for ETL/ELT orchestration. Proven experience with Qlik Replicate for log‑based CDC and real‑time data replication. Expert‑level SQL skills and strong experience with advanced enterprise data modeling techniques (Data Vault 2.0, Anchor Modeling). Strong understanding of enterprise data governance, metadata management, and data quality frameworks. Hands‑on experience with cloud platforms (AWS, Azure, or GCP) and enterprise data services. Strong architectural thinking, strategic planning, and stakeholder engagement skills. Highly Desirable Skills Experience designing Data Mesh or Data Fabric architectures. Knowledge of Data Lakehouse paradigms (Delta Lake, Apache Iceberg). Experience with enterprise cloud data platforms such as Snowflake, Redshift, BigQuery, or Synapse. Familiarity with Infrastructure as Code (Terraform, CloudFormation). Experience with IBM WatsonX platform (WatsonX Orchestrate or WatsonX.ai). Understanding of MLOps principles and large‑scale ML data provisioning. Experience integrating enterprise governance tools such as Collibra, Alation, or Informatica with virtualization platforms. Proficiency in Python or Scala for automation and custom data processing. Experience implementing CI/CD pipelines using Git, Jenkins, Azure DevOps, or Liquibase. Education Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field. Additional Information Employment Type: Full‑time Salary: Market Related / Negotiable Location: Johannesburg / Cape Town / Remote Must be located in South Africa or have a valid work permit for South Africa. #J-18808-Ljbffr