10 hours ago
6
Job Details
Department
Information Technology
Minimum experience
Mid-Senior
Company primary industry
FMCG
Job functional area
Information Technology
EE Status
Only open to EE candidates
Job Description
Sea Harvest is a proudly South African integrated fishing and food processing company, delivering quality seafood and food products to local and international markets. We are committed to sustainability, innovation and the development of our people.
An exciting opportunity exists for a suitably qualified and experienced Data Engineer to join our team.
ROLE OVERVIEW:
The Data Engineer is responsible for designing, building and maintaining scalable data pipelines and data platforms that provide reliable, secure and high-quality data for analytics, reporting and advanced insights. The role focuses on ingesting, transforming and structuring data from multiple source systems into curated datasets that support business intelligence, analytics, automation and informed decision-making across Sea Harvest. This position requires strong technical expertise in data engineering principles, cloud-based data platforms, and collaboration with BI analysts, data scientists, and business stakeholders to ensure data solutions are fit for purpose, performant, and aligned with business requirements.
The successful candidate will work closely with BI, Analytics, Automation and business teams to translate data requirements into robust technical solutions, while maintaining strong standards for data quality, governance, security, performance and documentation.
KEY ACCOUNTABILITIES:
Data Pipeline & Platform Engineering
Design, develop, and maintain robust and scalable data pipelines (batch and near-real-time) from multiple source systems.
Build and optimize ETL/ELT processes to ingest, cleanse, transform, and model data for analytical use cases.
Implement data orchestration, scheduling, and monitoring to ensure reliability and data freshness.
Optimize performance, cost, and scalability of data pipelines and data storage solutions.
Data Warehousing & Modelling
Design and maintain enterprise data warehouse and lakehouse architectures.
Develop dimensional and analytical data models to support reporting, dashboards, and advanced analytics.
Ensure data consistency, traceability, and lineage across data layers (raw, curated, presentation).
Collaborate with BI analysts to ensure datasets are structured for efficient consumption.
Data Quality, Governance & Security
Implement data quality checks, validation rules, and exception-handling mechanisms.
Enforce data governance standards, naming conventions, and documentation practices.
Ensure data security, access controls, and compliance with internal policies and regulatory requirements.
Support the auditing and monitoring of data usage and integrity.
Collaboration & Stakeholder Engagement
Work closely with BI, analytics, automation, and business teams to understand data requirements.
Translate business needs into technical data solutions and architectures.
Provide technical guidance and support on data-related best practices.
Assist with troubleshooting data issues and root cause analysis.
Continuous Improvement & Innovation
Identify opportunities to improve data architecture, tooling, and processes.
Stay up to date with emerging data engineering technologies and industry best practices.
Contribute to automation, standardisation, and reusable data engineering components.
QUALIFICATIONS & REQUIREMENTS:
Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
Microsoft certifications in Data Engineering, Azure, Fabric, or related technologies are highly desirable.
Experience with Microsoft Fabric, Azure data services, or similar cloud data platforms is required.
At least 3–5 years of hands-on experience in data engineering, data warehousing, or related roles
KEY COMPETENCIES:
Strong proficiency in SQL and data modelling techniques.
Experience building ETL/ELT pipelines using modern data engineering tools and frameworks.
Working knowledge of Microsoft Fabric, including Data Factory, Lakehouse, and Warehouse, or equivalent platforms.
Experience with Python, Spark, or similar data processing technologies.
Understanding of cloud data architectures, APIs, and system integrations.
Strong problem-solving and analytical thinking skills.
Ability to work independently and collaboratively within cross-functional teams.
Good verbal and written communication skills.
Well organised, with an understanding of business processes and data flows.
Solid understanding of planning and project delivery principles.
Attention to detail; self-motivated; able to work under pressure.
Ability to explain complex technical concepts to non-technical stakeholders.
Important:
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