Principal Data Architect

About the role

SHAPE THE FUTURE OF AI & DATA WITH US

At Datatonic, we are Google Cloud's premier partner in AI, driving transformation for world-class businesses. We push the boundaries of technology with expertise in machine learning, data engineering, and analytics on Google Cloud. By partnering with us, clients future-proof their operations, unlock actionable insights, and stay ahead of the curve in a rapidly evolving world.

YOUR MISSION

As a Principal Data Architect, you will play a pivotal role in designing and implementing modern, scalable data solutions for our clients. Working closely with colleagues across the Data & Analytics Engineering teams, you will help architect, build, and optimise new data platforms or migrate existing solutions to Google Cloud.

This is an exciting opportunity for a highly-experienced data professional who is passionate about leveraging cloud technologies to drive innovation and efficiency. You will consult with our clients to understand their business needs and objectives, gather requirements, and define and deliver robust, high-performance data architectures. If you thrive in a fast-paced, technology-driven, consulting environment and are eager to make a tangible impact on transformative projects, this role is for you.

WHAT YOU’LL DO

- Design & Deliver Cutting-Edge Data Solutions – Lead the analysis, design, and execution of state-of-the-art, data-driven solutions to meet our client’s business needs, leveraging the best of Google Cloud technologies.

- Data Architecture & Governance – Serve as an expert in data transformation, storage, retrieval, security, and governance, ensuring scalable, secure, and efficient data solutions.

- Guide & Mentor Engineers – Provide architectural direction to engineers, ensuring they build robust, high-performance solutions aligned with your target data architecture.

- Master Data Modeling Techniques – Apply expertise in various data modeling approaches, including 3NF, Data Vault, Star Schema, and One Big Table (OBT). Clearly articulate the benefits and trade-offs of each method and optimize their implementation within columnar databases such as BigQuery.

- Shape Data Strategy – Collaborate with the client to define and refine data strategy, covering: - Data governance and compliance - Scalable and efficient data modeling techniques - Ensuring data quality and integrity - Data management, security, and privacy best practices - Establishing optimal workflows and operational efficiencies

- Develop Fully Integrated Solutions – Work alongside Architecture, Engineering, and Data Science teams to design comprehensive, production-ready solutions that incorporate: - Cloud best practices - Scalable and efficient ingestion strategies - Feature engineering methodologies - End-to-end production readiness

- Leverage Leading Technologies – Design and implement solutions using key partner technologies, including: - Google Cloud – BigQuery, Dataflow, Vertex AI, and more - dbt Labs – Modern analytics engineering and transformation - Snowflake – Cloud-native data warehousing - Fivetran – Automated data pipelines for seamless integration