About the Role
We are seeking a highly experienced Senior Enterprise Data Engineer to join our enterprise data leadership team. This is a strategic, senior-level position 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
- 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
- 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)
- 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
- 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 related technical field
Additional Information
- Employment Type: Full-time
- Salary: Market Related/ Negotiable
- Location Options: Johannesburg / Cape Town / Remote
- Must be located in South Africa or have a valid work permit for South Africa