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.

Data Engineering Architect Databricks