Job Description

Overview

We are looking for a highly experienced Senior Data Engineer / Technical Lead to take ownership of the architecture, design, and technical direction of a modern enterprise data platform built on Azure Databricks. This role will serve as the technical right-hand to the engineering leadership team, providing technical guidance to a team of approximately six engineers while driving key architectural decisions across the platform.

The successful candidate will play a critical role during the early stages of the program, leading the design of the central data model and data products, establishing architectural standards, and ensuring alignment across business and technical stakeholders.

Key Responsibilities

• Own the technical architecture, design, and implementation approach for the enterprise data platform.
• Define and drive the overall Azure Databricks strategy, architecture, and engineering standards.
• Translate business and product requirements into scalable, maintainable, and high-performing technical solutions.
• Lead technical decision-making and provide architectural guidance across the engineering team.
• Mentor and coach data engineers, promoting engineering excellence and best practices.
• Design and establish the central data model and data product framework for the platform.
• Create solution designs, architecture blueprints, and technical documentation.
• Present and defend architectural decisions to business stakeholders, architects, and senior leadership.
• Define development standards, governance frameworks, and engineering best practices.
• Ensure solutions are scalable, secure, cost-effective, and aligned with long-term business objectives.

Required Experience & Skills

• Extensive hands-on experience with Azure Databricks in enterprise-scale environments.
• Deep expertise in Lakehouse architecture and Medallion Architecture (Bronze, Silver, Gold).
• Strong experience designing and implementing enterprise data platforms.
• Proven track record in data modeling, semantic modeling, and data product design.
• Expert knowledge of Apache Spark, PySpark, Python, and SQL.
• Strong understanding of distributed data processing and modern data architecture patterns.
• Experience designing scalable, cloud-native analytics and data platforms.
• Ability to balance architectural vision with hands-on engineering delivery.
• Strong communication and stakeholder management skills.
• Experience presenting technical solutions to both technical and non-technical audiences.

Nice to have

• Experience with Azure Data Lake Storage, Unity Catalog, Delta Lake, and related Databricks services.
• Knowledge of data governance, security, and data quality frameworks.
• Experience leading or mentoring engineering teams.
• Familiarity with Data Mesh and modern data product operating models.
• Azure and Databricks certifications are highly desirable.