Azure Databricks Solution Architect

Infosys

Bengaluru

On-site

INR 1,500,000 - 2,100,000

Full time

14 days+
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Job summary

Infosys is seeking a senior Data Engineering/Architecture professional to lead enterprise Azure Databricks initiatives in Bengaluru. You will design data pipelines, govern standards, and drive modernization across cloud platforms, including Lakehouse and Delta Lake architectures.

The role requires deep hands-on expertise with PySpark, Spark, Python, SQL, and Azure ecosystem tools. You will mentor teams and collaborate with stakeholders on solution roadmaps.

Qualifications

  • Lead architecture, design, and implementation of enterprise-scale Azure Databricks solutions.
  • Define and govern modern Data Engineering and Data Architecture standards.
  • Design scalable ETL/ELT frameworks, data pipelines, and cloud-native data platforms.
  • Architect solutions using Azure Databricks, PySpark, Azure Data Factory, ADLS Gen2, and Azure Synapse Analytics.
  • Build and optimize large-scale Data Lake, Delta Lake, and Lakehouse Architecture implementations.
  • Drive cloud migration and modernization initiatives from legacy platforms to Azure.
  • Collaborate with business leaders, enterprise architects, and delivery teams to define solution roadmaps.
  • Lead performance optimization, scalability improvements, and platform modernization efforts.
  • Establish best practices around Data Governance, Security, Data Quality, and Compliance.
  • Support project estimation, solution reviews, architecture governance, and technical presales activities.
  • Mentor Data Engineers and technical teams on Azure and Databricks best practices.
  • Evaluate emerging Azure and Databricks capabilities to enable innovation and platform optimization.

Responsibilities

  • Lead architecture, design, and implementation of enterprise-scale Azure Databricks solutions.
  • Define and govern modern Data Engineering and Data Architecture standards.
  • Design scalable ETL/ELT frameworks, data pipelines, and cloud-native data platforms.
  • Architect solutions using Azure Databricks, PySpark, Azure Data Factory, ADLS Gen2, and Azure Synapse Analytics.
  • Build and optimize large-scale Data Lake, Delta Lake, and Lakehouse Architecture implementations.
  • Drive cloud migration and modernization initiatives from legacy platforms to Azure.
  • Collaborate with business leaders, enterprise architects, and delivery teams to define solution roadmaps.
  • Lead performance optimization, scalability improvements, and platform modernization efforts.
  • Establish best practices around Data Governance, Security, Data Quality, and Compliance.
  • Support project estimation, solution reviews, architecture governance, and technical presales activities.
  • Mentor Data Engineers and technical teams on Azure and Databricks best practices.
  • Evaluate emerging Azure and Databricks capabilities to enable innovation and platform optimization.

Skills

Azure Databricks
PySpark
Apache Spark
Spark SQL
Python
SQL
Azure Data Factory
ADLS Gen2
Azure Synapse Analytics
Lakehouse Architecture
Delta Lake
Databricks

Education

Bachelor of Engineering
BTech
BCA
BSc
ME
MTech
MCA
MSc
MBA

Tools

Terraform
ARM Templates

Job description

Educational Requirements

Bachelor of Engineering,BTech,BCA,BSc,ME,MTech,MCA,MSc,MBA

Service Line

Data Analytics Unit

Responsibilities
  • Lead architecture, design, and implementation of enterprise-scale Azure Databricks solutions.
  • Define and govern modern Data Engineering and Data Architecture standards.
  • Design scalable ETL/ELT frameworks, data pipelines, and cloud-native data platforms.
  • Architect solutions using Azure Databricks, PySpark, Azure Data Factory, ADLS Gen2, and Azure Synapse Analytics.
  • Build and optimize large-scale Data Lake, Delta Lake, and Lakehouse Architecture implementations.
  • Drive cloud migration and modernization initiatives from legacy platforms to Azure.
  • Collaborate with business leaders, enterprise architects, and delivery teams to define solution roadmaps.
  • Lead performance optimization, scalability improvements, and platform modernization efforts.
  • Establish best practices around Data Governance, Security, Data Quality, and Compliance.
  • Support project estimation, solution reviews, architecture governance, and technical presales activities.
  • Mentor Data Engineers and technical teams on Azure and Databricks best practices.
  • Evaluate emerging Azure and Databricks capabilities to enable innovation and platform optimization.
Required Skills
  • 1214 years of experience in Data Engineering, Data Architecture, and Cloud Data Platforms.
  • Strong expertise in Azure Databricks and enterprise-scale Databricks implementations.
  • Deep hands-on experience with PySpark, Apache Spark, Spark SQL, Python, and SQL.
  • Extensive knowledge of Azure Data Factory (ADF), Azure Data Lake Storage (ADLS Gen2), and Azure ecosystem services.
  • Proven experience designing and implementing Lakehouse Architecture and Delta Lake solutions.
Technical and Professional Requirements
  • Experience with Azure Synapse Analytics and enterprise analytics platforms.
  • Exposure to Structured Streaming, Real-Time Data Processing, and Event-Driven Architectures.
  • Knowledge of Medallion Architecture and modern Data Mesh concepts.
  • Experience with multi-cloud environments including AWS and GCP.
  • Familiarity with Infrastructure as Code (Terraform, ARM Templates).
  • Experience leading cloud migration and digital transformation programs.
Preferred Skills
  • Technology->Cloud Platform->Azure Networking Services->Azure;CDN
  • Technology->Data Engineering->Databricks
  • Technology->Big Data - Data Processing->PySpark
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