$150K - 200K a year
Lead design and implementation of scalable Databricks data lakehouse architecture, mentor data engineering teams, and ensure secure, optimized data pipelines.
Expertise in Databricks, data lakehouse architecture, cloud services (AWS), real-time data processing, security practices, and leadership in data engineering.
Position: Databricks Lead/Architecture Location: Remote Duration: Long Term Architecture & Design Define and design end-to-end data Lakehouse architecture leveraging Databricks, Delta Lake, and cloud-native services. Create reference architectures for batch, real-time, and streaming data pipelines. Architect data ingestion, curation, storage, and governance frameworks. Ensure the platform is scalable, secure, and optimized for performance and cost. Establish standards for data lineage, metadata management, and compliance. Work with enterprise architects to align Databricks solutions with overall cloud strategy (AWS). Leadership & Delivery Lead and mentor a team of data engineers in building robust data pipelines. Collaborate with data scientists, BI teams, and business stakeholders to enable advanced analytics and AI/ML use cases. Drive adoption of DevOps and CI/CD practices for data engineering. Review designs and solutions to ensure adherence to architectural principles. Implementation & Optimization Build, optimize, and manage large-scale PySpark/SQL pipelines in Databricks. Enable real-time data processing through Kafka, Kinesis, or Event Hubs. Implement security best practices including RBAC, data masking, and encryption.
This job posting was last updated on 10/8/2025