Databricks Solution Architect Champion

TechYard; Greater London; On-site; GBP 70,000 - 90,000; Full time

Job summary

A leading consultancy is seeking a Databricks Champion Solution Architect to lead advanced data and AI solutions on the Databricks Lakehouse Platform. This role involves designing scalable data pipelines, mentoring teams, and ensuring best practices in data engineering. Ideal for a seasoned professional with expertise in Databricks and Apache Spark, this position offers the chance to drive innovation and shape the consultancy's data capabilities.

Qualifications

• Expertise with Databricks and Apache Spark in production environments.
• Experience with version control and automated deployment pipelines.

Responsibilities

• Architect and implement scalable data and AI solutions using Databricks.
• Drive performance tuning and cost optimisation across data workloads.

Skills

Leadership

Problem Solving

Communication

Education

Databricks certifications

Tools

Apache Spark

PySpark

SQL

GitHub Actions

Azure DevOps

MLflow

dbt

Power BI

Tableau

Job description

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Senior Delivery Consultant @ TechYard Recruitment | Connecting Talent to Opportunity

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.

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.
• 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.
• 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.

Seniority level

• Seniority level

  Not Applicable

Employment type

• Employment type

  Full-time

Job function

• Job function

  Consulting

• Industries

  IT Services and IT Consulting and Business Consulting and Services

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