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Tech Lead – Azure Databricks Data Platform
Job in
City Of London, Central London, Greater London, England, UK
Listed on 2026-07-11
Listing for:
Eaglecliff
Full Time
position Listed on 2026-07-11
Job specializations:
-
IT/Tech
Data Engineering
Job Description & How to Apply Below
Overview
Exciting opportunity for a dynamic Data Technical Lead with strong Databricks experience and Azure to join a leading energy trading company. The role focuses on Azure Data Platform and Databricks with emphasis on delivering scalable, enterprise data solutions.
Responsibilities- Lead the design, development, and implementation of scalable, high-performance data solutions on Azure and Databricks.
- Define and drive data strategy, governance, data quality, and platform best practices.
- Optimize platform runtime performance and manage cloud costs, with a focus on Databricks streaming workloads.
- Provide end-to-end technical leadership from solution architecture through delivery and production support.
- Collaborate with business stakeholders to translate requirements into robust technical solutions.
- Demonstrate ownership, accountability, and stakeholder management skills.
- Apply relevant experience in the financial trading domain, including trading data models and related business processes.
- Drive technical decision-making, mentor engineering teams, and ensure delivery of business outcomes.
- Communicate effectively and influence technical direction while delivering complex data solutions from concept to implementation.
- Extensive experience with Azure Data Platform and Databricks.
- Hands-on expertise with Structured Streaming, Delta Live Tables (DLT), PySpark, Python, and SQL.
- Proven track record delivering large-scale enterprise data platforms.
- Strong leadership and mentoring capabilities, with the ability to guide engineering teams and stakeholders.
- Excellent communication skills and ability to translate business requirements into technical solutions.
- Experience with in the financial trading domain and knowledge of trading data models and processes.
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