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.
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