Data Engineer

Job Description

Key Responsibilities
Design, build, and maintain high‑quality Gold layer data models that are analytics‑ready and aligned to business requirements.
Apply medallion architecture principles (Bronze, Silver, Gold) to deliver scalable, well‑structured data solutions.
Develop and optimise data transformations using PySpark and SQL.
Establish, maintain, and troubleshoot API-based data integrations across different environments.
Design data models that support reporting, analytics, and downstream consumption, working closely with analysts and BI developers.
Promote and support pipelines across multiple environments (e.g. dev, test, prod), including managing environment‑specific configurations and deployments.
Work effectively within an Agile delivery model, contributing to sprint planning, reviews, and iterative delivery.
Collaborate with analytics, engineering, and business stakeholders to translate requirements into reliable data solutions.
Contribute to documentation and promote best practices in data engineering and modelling.

Required Skills and Experience
Strong hands-on experience with medallion architecture and layered data platform design.
Proficiency in PySpark and SQL.
Strong understanding of prompt engineering and data agents
Proven experience establishing and managing API integrations across environments.
Experience designing analytics‑friendly data models (e.g. facts, dimensions, curated datasets).
Previous experience working in an Agile methodology (Scrum / Kanban).

Soft Skills
Excellent communication skills, with the ability to clearly explain technical concepts to both technical and non‑technical audiences.
Strong collaboration skills and a proactive approach to problem-solving.

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