Lead Data Engineer - Databricks

Lead Data Engineer - Databricks:

Do you want to have an immediate impact on customers and colleagues?

I am now working with an AI first consultancy in Copenhagen who are looking to strengthen their tight-knit team with a new senior specialist 💪

Building comprehensive data platforms that became the backbone of their customers data-driven decision making.

Leveraging modern data platform solutions like Snowflake, BigQuery, and Databricks. Being both key advisors and technical specialists with the aim of offering advanced insights throughout the project lifecycle.

Being in a small team means there is a healthy balance of independent project management as well as highly collaborative, team focuses tasks.

Responsibilities:

• Design, build, and optimize data pipelines and lakehouse architectures on Databricks (Delta Lake, Unity Catalog, Workflows).
• Lead and manage client projects, ensuring timely and high-quality delivery of data platform solutions.
• Collaborate with clients to understand their business needs and translate them into scalable technical solutions.
• Write production-grade Spark (PySpark or Spark SQL) for data transformation at scale.
• Implement medallion architectures, data quality frameworks, and governance patterns using Unity Catalog.
• Integrate Databricks with the broader Azure ecosystem (ADLS, Data Factory, Key Vault, Entra ID).
• Develop and maintain data models, pipelines, and orchestration across client environments.
• Explore and implement advanced techniques in GenAI and ML using Databricks capabilities (MLflow, Model Serving).
• Mentor and guide team members, fostering a culture of continuous learning and improvement.

Requirements:

• Extensive hands-on experience with Databricks — including Delta Lake, Unity Catalog, and Databricks Workflows/Jobs.
• Strong proficiency in PySpark or Spark SQL, writing clean and testable code at scale.
• Solid experience with Azure cloud services (ADLS, ADF, DevOps, Key Vault).
• Experience in data warehousing, modeling, and pipeline development.
• Proficiency in SQL, Python, and working with APIs.
• Knowledge of complementary tools in the modern data stack (e.g. dbt, Snowflake, Power BI) is a strong plus.
• Experience with infrastructure-as-code (Terraform or Databricks Asset Bundles) is a plus.
• Experience with GenAI/Machine Learning/MLOps is seen as a plus.
• Excellent problem-solving abilities and attention to detail.
• Strong communication skills in English; Danish is a plus but not required.
• Ability to manage multiple projects and deliver results in a consulting environment.
• Fluency in Danish

This is a broad requirement and we don't expect to find someone who ticks every box. If you are an ambitious data professional who wants to have their say on new data-driven decision making designed to support AI then lets talk!

[email protected]