Tech Lead - Data Bricks

We are seeking a skilled Databricks Architect to design, implement, and optimize scalable data solutions within our cloud-based data platform. This role requires extensive knowledge of Databricks (Azure / AWS), data engineering, and a deep understanding of data architecture principles, with the ability to drive strategy, best practices, and hands-on implementation for high-performance data processing and analytics solutions.

Responsibilities :

• Solution Architecture :
• Design and architect end-to-end data solutions using Databricks and Azure / AWS, including data ingestion, processing, and storage.
• Delta Lake Implementation :
• Leverage Delta Lake and Lakehouse architecture to create robust, unified data structures that support advanced analytics and machine learning.
• Data Processing Development :
• Develop, design, and automate large-scale, high-performance data processing systems (batch and / or streaming) to drive business growth and enhance the product experience.
• Performance Tuning :
• Ensure optimal performance of data pipelines and workloads by implementing best practices for resource management, auto-scaling, and query optimization in Databricks.
• Engineering Best Practices :
• Advocate for high-quality software engineering practices in building scalable data infrastructure and pipelines.
• Architecture / Solution Development :
• Develop Architecture or solution for large data project using Databricks.
• Project Leadership :
• Lead data engineering projects to ensure pipelines are reliable, efficient, testable, and maintainable.
• Data Modeling :
• Design data models optimized for storage, retrieval, and critical product and business requirements.
• Logging Architecture :
• Understand and influence logging to support data flow, implementing logging best practices as needed.
• Standardization and Tooling :
• Contribute to shared data engineering tools and standards to boost productivity and quality for Data Engineers across the company.
• Collaboration :
• Work closely with leadership, engineers, program managers, and data scientists to understand and meet data needs.
• Partner Education :
• Use data engineering expertise to identify gaps and improve existing logging and processes for partners.
• Data Governance :
• Collaborate with stakeholders to build data lineage, data governance, and data cataloging using unity catalog.
• Agile Project Management :
• Lead projects using agile methodologies.
• Communication :
• Communicate effectively with stakeholders at all organizational levels.
• Team Development :
• Recruit, retain, and develop team members, preparing them for increased responsibilities and challenges.

Requirements :

Skills Required

Data Modeling, Spark, Databricks, Azure, Aws, Etl