Head of Data Platforms & Engineering

Blue Pearl HQ

Johannesburg

On-site

ZAR 1,100,000 - 1,900,000

Full time

9 days ago

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Job summary

Blue Pearl HQ is seeking an experienced Data Engineering Lead to design, build, and lead enterprise-scale data platforms that enable business intelligence, advanced analytics, reporting, and data-driven decision-making.

The successful candidate will provide technical leadership across the full data engineering lifecycle, collaborating with stakeholders, solution architects, BI teams, governance specialists, and software engineering teams to deliver trusted and analytics-ready data assets.

Qualifications

8–10+ years' experience in Data Engineering.
Minimum 3 years leading technical data engineering teams.
Experience designing enterprise-scale cloud data platforms.
Proven experience building scalable ETL/ELT solutions.
Experience working within enterprise environments.
Strong experience delivering complex data integration solutions.
Experience supporting reporting, analytics, and data science initiatives.
Experience implementing data governance frameworks.

Responsibilities

Lead the design, development, implementation, and continuous improvement of enterprise-grade data engineering solutions.
Architect scalable, secure, reusable, and high-performance data pipelines supporting batch and near real-time processing.
Provide technical leadership across multiple data engineering initiatives and mentor junior and intermediate engineers.
Establish and enforce enterprise data engineering standards, frameworks, and best practices.
Drive innovation and continuous improvement across the organisation's data platform capabilities.
Design robust ingestion frameworks for structured, semi-structured, and unstructured data.
Develop scalable storage architectures supporting data warehousing and lake house environments.
Implement efficient ETL and ELT processing frameworks.
Optimize cloud-native data architectures for performance, scalability, reliability, and cost efficiency.
Design resilient solutions supporting analytics, reporting, AI, and machine learning initiatives.
Build, maintain, and optimize enterprise data pipelines.
Develop complex SQL queries, stored procedures, and transformation logic.
Design and maintain reusable data integration components.
Perform data transformation, cleansing, enrichment, and validation processes.
Ensure consistent data availability and integrity across enterprise platforms.
Embed data quality controls throughout the engineering lifecycle.
Implement automated validation, monitoring, lineage, metadata management, and observability.
Ensure compliance with organizational governance frameworks and regulatory requirements.
Secure sensitive and confidential information through appropriate engineering controls.
Maintain Technical Documentation Including: Source-to-target mappings, Data dictionaries, Data lineage, Technical specifications, Data models, Pipeline documentation.