Principal Data Engineer

About the Opportunity

Vomela, a dynamic visual communications firm dedicated to crafting impactful brand solutions and nurturing client relationships, is actively seeking a Principal Data Engineer to join their remote team. This role is ideal for a technically adept and innovative individual who thrives on translating complex data challenges into elegant, reliable solutions. Vomela prioritises its people, offering a supportive environment where employees are encouraged to pursue careers they are passionate about while contributing to significant projects for both local and global brands.

What You'll Be Doing

As a Principal Data Engineer, you will play a pivotal role in shaping Vomela's data architecture and ensuring the integrity and accessibility of its data assets. Your responsibilities will span the entire data lifecycle, from design and implementation to ongoing maintenance and optimisation. This includes meticulously designing and deploying dimensional data models, such as star and snowflake schemas, to support robust business intelligence and reporting needs.

You will be instrumental in building and maintaining semantic models that serve as the definitive source of truth for all organisational reporting, ensuring consistency and accuracy across the board. A key aspect of this role involves managing master data engineering, establishing golden record patterns, defining authoritative sources of data, and implementing strategies for cross-system identity resolution. You'll also be responsible for setting and upholding data modelling standards across the engineering team, fostering a culture of best practice.

Furthermore, you will design and operate both real-time and near-real-time data pipelines, leveraging streaming technologies like Kafka or Confluent Cloud. A critical part of this is understanding when streaming is the most appropriate solution and when alternative approaches are more effective. You will relentlessly focus on minimising data staleness in non-streaming scenarios by optimising scheduling, implementing intelligent incremental load strategies, and architecting efficient pipeline orchestrations.

Performance tuning across the data stack will be a core function, encompassing query optimisation, partitioning strategies, indexing, Delta table compaction, and ensuring the efficiency of semantic model refreshes and Direct Lake readiness. Operational engineering discipline is paramount; you will define and implement robust observability, alerting mechanisms, Service Level Agreements (SLAs), failure recovery protocols, and capacity planning. You will also design and implement stringent controls for sensitive data, including financial information, personally identifiable information (PII), and data subject to HIPAA regulations, ensuring compliance and security.

What You'll Bring

Vomela is looking for a seasoned professional with a proven track record in data engineering. Essential technical expertise includes a deep understanding of Microsoft Fabric components such as Lakehouses, Notebooks, Dataflows Gen2, Eventstreams, Semantic Models, and Direct Lake mode. Proficiency in Power BI, specifically in report development and semantic model design with strong DAX skills, is also required.

Experience with relational databases like SQL Server, Azure SQL, or PostgreSQL, including query optimisation, schema design, and stored procedure development, is crucial. Familiarity with Azure DevOps for Git-based development workflows and CI/CD implementation for data pipelines is expected.

Demonstrated experience in utilising AI coding assistants within a production engineering environment is a significant advantage. You should possess the ability to critically evaluate, edit, and refine AI-generated code and artefacts, understanding both the benefits and the inherent risks. A clear grasp of how AI can accelerate development while also identifying potential pitfalls is essential.

The ideal candidate will possess a comprehensive understanding of building scalable, observable, and resilient data pipelines. This includes expertise in watermarking for incremental loads, Change Data Capture (CDC) patterns, and designing both batch and streaming architectures. A strong technical voice in code reviews, capable of providing impactful feedback and ensuring high code quality, is also a key requirement. Ultimately, you should be adept at translating intricate business requirements into user-friendly semantic models and report-layer components that non-technical stakeholders can confidently navigate and trust.

In South Africa, principal data engineer roles typically command competitive salaries, reflecting the specialised skills and experience required. Common employers include large enterprises in the financial services, telecommunications, and retail sectors, as well as growing tech startups. This position offers significant career progression opportunities, with potential to move into data architecture leadership or specialised AI/ML engineering roles within an organisation.

• Microsoft Fabric: Lakehouses, Notebooks, Dataflows Gen2, Event streams, Semantic Models, Direct Lake mode
• Power BI: report development, dataset/semantic model design, DAX proficiency
• SQL Server / Azure SQL/Postgres: query optimization, schema design, stored procedures
• Azure DevOps: Git-based development workflows, CI/CD for data pipelines
• Demonstrated use of AI coding assistants in a production engineering workflow
• Ability to critically evaluate, edit, and improve AI-generated code and artifacts
• Clear understanding of where AI accelerates work and where it introduces risk