Description

Key responsibilities

• Own the end-to-end architecture for Azure Databricks-based data platforms, including ingestion, transformation, storage, serving, and governance layers.
• Design reusable frameworks, ELT patterns, and data models that improve delivery speed, consistency, and maintainability.
• Build and optimize pipelines and Spark jobs directly, with a strong focus on performance, reliability, and cost efficiency.
• Architect solutions using Azure Databricks, Delta Lake, ADLS, Azure Data Factory, and related Azure platform services.
• Establish governance, security and code-quality standards for the platform.
• Partner closely with business analysts, functional teams, and engineering teams to translate requirements into working solutions.
• Guide troubleshooting, code reviews, and production support for complex data workloads.
• Drive modernization and cloud-native adoption across data and analytics capabilities.

Must-have qualifications

• 12+ years of experience in data engineering, data architecture, or platform engineering.
• Strong hands-on experience with Azure Databricks, Spark, Python/Scala, SQL, and Delta Lake.
• Proven experience designing and implementing cloud data hubs, data lakes, and analytical data stores.
• Experience with Azure DevOps, CI/CD, and automated deployment practices.
• Ability to work directly on technical implementation, not only provide oversight.
• Strong communication and stakeholder collaboration skills.

Preferred qualifications

• Experience in financial services or insurance.
• Knowledge of Event Hub, Cosmos DB, Azure Synapse, or other Azure analytics services.
• Databricks or Microsoft Azure certifications.
• Experience with reusable frameworks, shell scripting, and production support in large-scale environments

Key Skills

Education

Bachelor's degree