Senior Data Platform Engineer

We are looking for an experienced Senior Data Platform Engineer to design, build, and own scalable data platforms and production-grade data systems. You will take end-to-end ownership of data pipelines and architecture while working closely with software engineers and stakeholders to support operational, analytical, and future AI-driven use cases.

• Working Hours: Mon-Fri
• Working Location: Central
• Job Type: Contract
• Salary Package: Up to $11,000 (basic) + AWS

Key Responsibilities

• Own the end-to-end design, development and delivery of data pipelines, covering data ingestion, transformation, processing and serving.
• Design scalable data models, storage solutions and architectures supporting both operational and analytical workloads.
• Build and maintain frameworks and infrastructure for data quality, observability, monitoring and governance.
• Develop reliable, production-grade data systems with a strong focus on scalability, maintainability and performance.
• Contribute to overall product, data and platform architecture, collaborating with software engineers across different areas as priorities evolve.
• Design extensible data platforms capable of supporting future AI/ML and retrieval-based applications, including RAG use cases.
• Play a key role in technical architecture and engineering decisions, identifying and communicating technical trade-offs and risks.
• Collaborate with technical and business stakeholders on platform architecture, infrastructure and deployment decisions.
• Ensure appropriate handling of sensitive data, security requirements and system constraints within a regulated environment.
• Apply sound software engineering practices across system design, APIs, testing, deployment and production support.

Requirements

• 5–7+ years of professional software engineering/data engineering experience, with demonstrated ownership of production data systems from design through deployment and operations.
• Strong knowledge of data engineering fundamentals, including ETL/ELT pipelines, data modelling, batch processing and streaming architectures.
• Strong proficiency in at least one general-purpose programming language such as Python, Java, Scala, Go or equivalent.
• Proven experience developing production-grade backend applications or systems, beyond standalone data scripts and pipelines.
• Good understanding of software engineering principles, including API design, system architecture, testing and maintainable code.
• Hands-on experience with cloud-native data platforms, modern data architectures or lakehouse solutions.
• Ability to work independently, take ownership of complex technical areas and contribute significantly to architectural decisions.
• Strong analytical, problem-solving and troubleshooting capabilities.
• Strong communication and stakeholder management skills, with the ability to explain complex technical concepts and trade-offs to both technical and non-technical audiences.

Good to Have

• Experience with Databricks, Unity Catalog, Delta Lake or comparable lakehouse technologies.
• Experience developing data pipelines supporting AI/ML or Retrieval-Augmented Generation (RAG) workloads, such as embedding generation, vector databases/vector stores and retrieval pipelines.
• Knowledge of data governance, metadata management, lineage and access-control practices.
• Experience working in government, public sector, financial services or other regulated environments involving sensitive data.
• Experience with cloud-native deployment platforms, containerisation and modern DevOps/CI/CD practices.
• Relevant cloud, data engineering or Databricks certifications would be advantageous.