Data Architect (AWS Databricks)

Role Overview

We are looking for a Data Architect to own the design and delivery of modern data platforms built on AWS and Databricks. This role combines deep hands-on engineering with team leadership, covering data ingestion, transformation, and warehousing across structured and unstructured sources.

Key Responsibilities

• Architect and deliver end-to-end data engineering solutions on AWS and Databricks, spanning ingestion, transformation, and warehousing layers.
• Design scalable pipelines for structured and unstructured data, balancing reliability, performance, and cost efficiency.
• Lead and mentor a team of data engineers, overseeing sprint planning, code quality, and technical delivery.
• Partner with architects and business stakeholders to translate requirements into robust, production-ready designs.
• Establish and maintain standards for data quality, governance, and platform scalability.

Must-have Skills

• AWS Services: Hands-on expertise across core AWS services spanning compute, storage, orchestration, and security in production environments.
• Databricks Platform: Deep proficiency in Databricks, including Delta Lake, Unity Catalog, cluster management, and job orchestration at scale.
• Data Engineering Lifecycle: Proven ability to design and operate ingestion, transformation, and warehousing pipelines across structured and unstructured data.
• Team Leadership: Experience leading and mentoring data engineering teams, managing delivery timelines, and driving technical quality.

Good-to-have Skills

• Agentic AI Exposure: Working understanding of agentic AI concepts and frameworks, and how they apply within modern data platforms.
• Manufacturing Industry Knowledge: Familiarity with manufacturing industry data landscapes, processes, and common use cases.
• Data Modelling: Understanding of data modelling principles, including dimensional and canonical modelling approaches.