Databricks Lead / Architect will own end-to-end solution design and provide hands-on technical
leadership across Databricks and cloud data platforms. The role involves translating business and data
requirements into scalable architectures, establishing engineering standards, guiding development
teams, driving modernization and migration initiatives, and working closely with clients, architects and
technology leadership.
Key Responsibilities
• Design and implement enterprise-scale Databricks Lakehouse architectures.
• Define architecture across Azure, AWS and GCP based on business and technical requirements.
• Design data ingestion, transformation and processing using Databricks, Spark, PySpark, SQL and
Python.
• Establish Lakehouse architecture, including Delta Lake, Medallion Architecture and data
modelling.
• Design batch and real-time data processing and integration solutions.Job Description
Experion Technologies Experion Confidential Page 2 of 3
DOC ID: Experion/TA/FM/02/V2.1
• Architect and implement Databricks Workflows, Jobs, Unity Catalog and governance
capabilities.
• Define data security, access control, lineage, quality, monitoring and governance standards.
• Design scalable and optimized solutions for performance and cloud cost.
• Lead migration and modernization of legacy data platforms to Databricks.
• Integrate Databricks with cloud-native services across Azure / AWS / GCP.
• Establish CI/CD, Git, DevOps and deployment standards for data engineering.
• Provide technical leadership through design reviews, code reviews and engineering standards.
• Guide and mentor Data Engineers and technical teams.
• Conduct POCs and evaluate new Databricks/cloud capabilities.
• Work with business stakeholders, project managers and enterprise architects to translate
requirements into technical solutions.
• Support estimation, solution proposals, technical presentations and client discussions.
• Adhere to the Information Security Management policies and procedures.Mandatory Skills• 10+ years of experience in Data Engineering / Data Architecture.• Strong hands-on experience with Databricks and Lakehouse architecture.• Strong knowledge of Apache Spark, PySpark, Python and SQL.• Experience with Delta Lake and Medallion Architecture.• Strong experience in data modelling, ETL/ELT and data integration.• Experience designing scalable batch and real-time data solutions.• Strong knowledge of at least one major cloud platform: Azure, AWS or GCP.• Understanding of cloud data services and integration patterns.• Experience with Databricks Workflows/Jobs and Unity Catalog.• Strong understanding of data security, governance, quality and lineage.• Experience with CI/CD, Git and DevOps practices.• Strong solution architecture and technical leadership skillsSourced from naukri
