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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