Job Description

Key Responsibilities

- Architect and develop end‑to‑end data pipelines on Azure using Databricks (Spark / PySpark)
- Design and maintain lakehouse architectures using Azure Data Lake + Delta Lake
- Build and optimize batch and streaming pipelines for large‑scale datasets
- Create and manage feature pipelines and curated datasets for AI/ML model training and inference
- Collaborate with data scientists and ML engineers to enable scalable ML workflows
- Support MLOps pipelines, including data versioning, feature stores, and model deployment readiness
- Optimize Databricks workloads for performance, scalability, and cost efficiency
- Implement data quality, validation, monitoring, and observability frameworks
- Ensure data security, governance, and compliance using Azure and Databricks best practices
- Review code, define standards, and mentor junior and mid‑level data engineers
- Lead architectural decisions and contribute to data platform roadmap planning

📌 Data Engineer : Advanced Engineer (Bengaluru)
🏢 Brady
📍 Bengaluru