Data Engineering Architect Databricks

Job Title: Data Engineering Architect – Databricks

Location: Bangalore, India

Work Mode: Work from Office

Experience: 7–12 Years

Industry: Retail

Employment Type: Full-Time

(Immediate joiner prefer )

Job Overview

We are looking for an experienced Data Engineering Architect with strong expertise in Databricks, PySpark, Python, SQL, Delta Lake, and Lakehouse architecture. The ideal candidate will have a strong background in designing scalable data engineering solutions, preferably within the retail domain.

Key Responsibilities

• Design and architect end-to-end data engineering solutions using Databricks, Delta Lake, and Lakehouse architecture.
• Develop and implement scalable and high-performance data pipelines using PySpark, Python, and SQL.
• Design data architectures supporting advanced analytics, AI, reporting, and business intelligence use cases.
• Establish best practices for data modelling, data cataloging, data quality, and data lifecycle management.
• Collaborate with business stakeholders, data scientists, architects, and engineering teams to translate business requirements into scalable technical solutions.
• Conduct architecture reviews and provide technical guidance and mentorship to data engineering teams.
• Ensure data solutions follow appropriate security, governance, quality, and compliance standards.
• Stay updated with emerging technologies and best practices in data engineering, Databricks, cloud platforms, and AI.

Mandatory Skills

• 7–12 years of experience in Data Engineering and/or Data Architecture.
• Strong experience working on Retail domain projects.
• Hands-on expertise in Databricks architecture and platform capabilities.
• Strong experience with Delta Lake and Lakehouse architecture.
• Advanced proficiency in PySpark, Python, and SQL.
• Strong understanding of data modelling, data cataloging, data quality, and data governance.
• Experience designing and implementing enterprise-scale data pipelines and platforms.
• Strong understanding of data engineering architecture and design principles.
• Excellent problem-solving, communication, and stakeholder management skills.
• BE/BTech in Computer Science, Engineering, or a related technical discipline.

Good to Have

• Experience with one or more cloud platforms: AWS, Azure, or GCP.
• Knowledge of Docker and Kubernetes.
• Databricks or cloud certifications.
• Exposure to machine learning model deployment and MLOps.
• Experience with enterprise data governance and security frameworks.
• Knowledge of CI/CD and DevOps practices for data engineering.
• Experience working with large-scale retail datasets and analytics platforms.