Databricks Architect

Infosys; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Infosys is seeking an experienced Databricks, Snowflake and PySpark Architect to design scalable cloud‑based data platforms and modern analytics solutions. You will lead enterprise data architecture, guide lakehouse implementations, and collaborate with stakeholders to deliver high‑performance, secure data ecosystems.

The role requires mentoring engineers, driving CI/CD, and overseeing cloud migrations across Azure, AWS and GCP, while optimizing costs and governance.

Qualifications

• 11+ years of experience in Data Engineering, Analytics, or Data Platform Architecture.
• Strong expertise in Databricks Lakehouse Platform.
• Extensive hands-on experience with Snowflake Data Cloud.
• Expert-level proficiency in PySpark and distributed data processing.
• Strong experience in designing enterprise-scale data lakes, data warehouses, and lakehouse architectures.

Responsibilities

• Define and drive enterprise-scale data architecture and modernization strategies.
• Design end-to-end cloud data platforms using Databricks, Snowflake, and modern data engineering frameworks.
• Architect scalable batch and real-time data processing pipelines for large datasets.
• Lead data lake, lakehouse, and data warehouse implementations.
• Provide architectural guidance on performance optimization, scalability, governance, security, and reliability.
• Work closely with business stakeholders to understand analytical and reporting requirements.
• Review technical designs, conduct architecture assessments, and establish best practices.
• Mentor data engineers and technical leads across project engagements.
• Lead technology evaluations, POCs, and solution accelerators.
• Drive cloud migration and modernization initiatives from legacy data platforms.
• Ensure adherence to enterprise security, compliance, and data governance standards.
• Collaborate with DevOps and platform teams to implement CI/CD and infrastructure automation for data solutions.

Tools

Databricks Lakehouse

Snowflake

PySpark

Data Architecture

Cloud Data Platforms

Leadership

Job description

Job Summary

We are seeking an experienced Databricks, Snowflake and PySpark Architect to design, architect, and deliver scalable cloud-based data platforms and modern analytics solutions. The ideal candidate will have deep expertise in data architecture, cloud-native technologies, data engineering best practices, and large-scale data transformation programs. The role involves collaborating with business stakeholders, solution architects, and engineering teams to build high-performance, secure, and cost-efficient data ecosystems leveraging Databricks, Snowflake, and PySpark.

Responsibilities

• Define and drive enterprise-scale data architecture and modernization strategies.
• Design end-to-end cloud data platforms using Databricks, Snowflake, and modern data engineering frameworks.
• Architect scalable batch and real-time data processing pipelines for large datasets.
• Lead data lake, lakehouse, and data warehouse implementations.
• Provide architectural guidance on performance optimization, scalability, governance, security, and reliability.
• Work closely with business stakeholders to understand analytical and reporting requirements.
• Review technical designs, conduct architecture assessments, and establish best practices.
• Mentor data engineers and technical leads across project engagements.
• Lead technology evaluations, proof-of-concepts (POCs), and solution accelerators.
• Drive cloud migration and modernization initiatives from legacy data platforms.
• Ensure adherence to enterprise security, compliance, and data governance standards.
• Collaborate with DevOps and platform teams to implement CI/CD and infrastructure automation for data solutions.

Technical Requirements

• 11+ years of experience in Data Engineering, Analytics, or Data Platform Architecture.
• Strong expertise in Databricks Lakehouse Platform.
• Extensive hands-on experience with Snowflake Data Cloud.
• Expert-level proficiency in PySpark and distributed data processing.
• Strong experience in designing enterprise-scale data lakes, data warehouses, and lakehouse architectures.
• Hands-on experience with cloud platforms such as Azure (ADF, ADLS Gen2, Synapse, Azure Databricks); AWS (S3, Glue, EMR, Redshift); GCP (BigQuery, DataProc, Cloud Storage).
• Strong SQL and data modeling skills (Dimensional Modeling, Data Vault, Star Schema).
• Experience building ETL/ELT frameworks and reusable data engineering accelerators.
• Knowledge of Data Governance, Metadata Management, Data Lineage, and Data Quality frameworks.
• Experience with orchestration tools such as Airflow, Azure Data Factory, or similar.
• Expertise in performance tuning and cost optimization within Databricks and Snowflake environments.
• Experience implementing CI/CD pipelines using Azure DevOps, GitHub Actions, Jenkins, or similar tools.

Additional Responsibilities

• Enterprise Data Architecture
• Solution Design Governance
• Technology Strategy Roadmap
• Presales Client Advisory
• Architecture Reviews
• Data Platform Modernization
• Technical Leadership Mentoring
• Cost Optimization Non-Functional Requirements
• Stakeholder Engagement

Educational Requirement

Bachelor of Engineering

Preferred Skills

• Technology->Data Engineering->Databricks

Service Line

Data Analytics Unit