Data Engineer - Tech Lead (Databricks, Pyspark)

We're looking for aSenior Data Engineer – Tech Lead (Databricks, PySpark) to join our team in London, UK, in a hybrid working mode.

In this role, you will lead the design, development and optimization of scalable cloud-native data architectures, focusing on Azure Databricks, PySpark and Lakehouse principles. You will work hands-on to deliver performant data solutions for high-volume workloads, ensuring governance, reliability and best practices for enterprise-grade platforms.

As a technical leader, you will define data strategies, drive modernization initiatives and mentor engineers, fostering excellence and innovation throughout the team. This position offers the opportunity to shape large-scale data ecosystems, implement modern engineering practices and enable next-generation analytics and AI-driven solutions.

Responsibilities

• Lead the architecture, design and build of large-scale data platforms using Azure Databricks and modern cloud technologies
• Implement and optimize ETL workflows and streaming pipelines with PySpark and Delta Live Tables following Lakehouse principles
• Enhance performance, manage cloud costs and ensure platform reliability for structured streaming workloads
• Define data governance, security and quality standards to maintain consistency across the platform
• Collaborate with stakeholders to translate complex business requirements into actionable technical solutions
• Develop integration approaches using Azure-native services such as Data Factory, Synapse and Blob Storage
• Mentor data engineers, promote modern engineering practices and perform technical reviews
• Drive adoption of CI/CD, Infrastructure as Code and automated testing in data engineering environments
• Implement observability and monitoring using tools like Databricks Workflows and related frameworks
• Contribute to AI-driven initiatives by leveraging Databricks ML/MosaicML to integrate Generative AI and LLM-based solutions

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering or related field
• Extensive experience designing and implementing production-grade platforms using Azure Databricks
• Expertise in PySpark, including advanced optimization, data skew mitigation and query tuning
• Strong programming skills in Python with knowledge of modern software design principles
• Practical experience with structured streaming, Delta Lake and Delta Live Tables
• Proven experience in Lakehouse migration and modernization using open table formats such as Delta Lake or Apache Iceberg
• Proficiency with cloud-native services on Azure and knowledge of multi-cloud environments (AWS or GCP)
• Hands-on experience with CI/CD and Infrastructure as Code tools (Terraform, GitHub Actions, Jenkins)
• Strong leadership ability to guide teams, define epics/user stories and ensure delivery in agile environments
• Excellent communication and stakeholder management skills for both technical and non-technical audiences

Nice to have

• Experience operationalizing LLM or Generative AI workflows in Databricks pipelines
• Familiarity with frameworks like LangChain, LlamaIndex or Databricks ML/MosaicML
• Knowledge of AI governance, security practices and enterprise integration controls
• Background in financial trading data or related domains
• Official Databricks certifications such as Certified Data Engineer Professional or Apache Spark Developer