Techyard is supporting a growing Databricks-partnered consultancy in securing a Databricks Champion Solution Architect to lead the design and delivery of advanced data and AI solutions on the Databricks Lakehouse Platform. This strategic, high-impact role is ideal for a seasoned professional who can operate as both a hands-on architect and a trusted advisor—bridging business vision with technical excellence. You’ll play a pivotal part in driving innovation, embedding best practices, and shaping the consultancy’s data engineering capabilities as they scale their team and client base.
If you are considering sending an application, make sure to hit the apply button below after reading through the entire description.
Key Responsibilities:
* Architect and implement end-to-end, scalable data and AI solutions using the Databricks Lakehouse (Delta Lake, Unity Catalog, MLflow).
* Design and lead the development of modular, high-performance data pipelines using Apache Spark and PySpark.
* Champion the adoption of Lakehouse architecture (bronze/silver/gold layers) to ensure scalable, governed data platforms.
* Collaborate with stakeholders, analysts, and data scientists to translate business needs into clean, production-ready datasets.
* Promote CI/CD, DevOps, and data reliability engineering (DRE) best practices across Databricks environments.
* Integrate with cloud-native services and orchestrate workflows using tools such as dbt, Airflow, and Databricks Workflows.
* Drive performance tuning, cost optimisation, and monitoring across data workloads.
* Mentor engineering teams and support architectural decisions as a recognised Databricks expert.
Essential Skills & Experience:
* Demonstrable expertise with Databricks and Apache Spark in production environments.
* Proficiency in PySpark, SQL, and working within one or more cloud platforms (Azure, AWS, or GCP).
* In-depth understanding of Lakehouse concepts, medallion architecture, and modern data warehousing.
* Experience with version control, testing frameworks, and automated deployment pipelines (e.g., GitHub Actions, Azure DevOps).
* Sound knowledge of data governance, security, and compliance, including Unity Catalog.
* Excellent communication, leadership, and problem-solving skills.
Desirable:
* Databricks certifications (e.g., Data Engineer Associate / Professional or Solutions Architect).
* Familiarity with MLflow, dbt, and BI tools such as Power BI or Tableau.
* Exposure to MLOps practices and deploying ML models within Databricks.
* Experience working within Agile and DevOps-driven delivery environments.