Solutions Architect

United HR Solutions Pvt. Ltd.; Bengaluru; On-site; INR 3,600,000 - 6,000,000; Full time

Job summary

United HR Solutions Pvt. Ltd. seeks a Resident Solution Architect - Databricks to design and lead enterprise-scale Data & AI solutions on the Databricks Lakehouse Platform.

You will drive end-to-end implementations across AWS/Azure/GCP, building scalable, secure data platforms and optimizing performance. The role requires 10+ years in consulting/tech, strong Databricks/Spark/Delta Lake expertise, and global enterprise experience.

Qualifications

• 10+ years of consulting and technology experience.
• Minimum 7+ years of experience in Data Engineering, Data Platforms, or Analytics.
• Minimum 6-8 enterprise Databricks implementations delivered in production environments.
• Hands-on enterprise delivery experience is mandatory.
• Strong experience designing and deploying large-scale distributed data platforms.
• Strong customer-facing consulting and solution architecture experience.
• Experience working with global enterprise customers across multiple industries.
• Strong expertise in Apache Spark, Databricks, Delta Lake, and modern data engineering practices.
• Experience with AWS, Azure, and/or GCP.
• Bachelor's degree in Computer Science, Engineering, Information Technology, or related discipline.
• Master's degree preferred.
• Databricks Data Engineer Professional Certification - Mandatory.
• Additional AWS, Azure, or GCP certifications are highly desirable.
• Excellent technical, communication, and presentation skills.
• Strong consulting and problem-solving mindset.
• Executive presence and stakeholder management capabilities.
• Strong customer engagement and workshop facilitation skills.
• Ability to influence technical and business decision-makers.

Responsibilities

• Design and lead enterprise-scale Data & AI solutions on the Databricks Lakehouse Platform.
• Architect scalable, secure, and high-performance data platforms across AWS, Azure, and/or GCP.
• Define end-to-end solution architecture aligned with business and technical objectives.
• Lead end-to-end enterprise Databricks implementations from discovery through production deployment.
• Deliver large-scale production workloads with focus on scalability, reliability, and performance.
• Solve complex challenges involving distributed data processing, platform optimization, and cloud-native architectures.
• Develop and optimize enterprise data pipelines using Apache Spark and Databricks.
• Build scalable ETL/ELT frameworks using Delta Lake and modern data engineering practices.
• Drive platform performance tuning, cost optimization, and workload scalability.
• Design and implement cloud-native data solutions across AWS, Azure, and GCP.
• Collaborate with platform engineering teams on CI/CD pipelines, deployment automation, Infrastructure-as-Code, and DevOps practices.
• Support enterprise MLOps implementation and integration with modern AI workflows.
• Lead architecture workshops, technical discovery sessions, and executive presentations.
• Partner with customers to understand business challenges and translate them into scalable technical solutions.
• Provide technical leadership throughout implementation and post-production support.
• Define enterprise architecture standards, implementation best practices, governance frameworks, and reusable solution accelerators.
• Ensure security, compliance, data quality, and operational excellence across implementations.
• Mentor engineering teams and contribute to organizational capability building.

Skills

Databricks

Apache Spark

Delta Lake

Cloud platforms

Solution architecture

Enterprise consulting

Stakeholder management

MLOps

CI/CD

DevOps

Education

Bachelor's degree in CS/Engineering/IT

Master's degree preferred

Tools

Databricks

Delta Lake

Job description

Company Details

Our client is an Data & AI / Business Consulting company

Designation

Resident Solution Architect - Databricks

Role Overview

We are looking for a Resident Solution Architect - Databricks with strong consulting, solution architecture, and enterprise Data & AI experience. The role involves designing and leading enterprise-scale data and AI solutions on the Databricks Lakehouse Platform, driving end-to-end Databricks implementations, and working closely with global enterprise customers to deliver scalable, secure, and high-performance data platforms.

Key Responsibilities

• Design and lead enterprise-scale Data & AI solutions on the Databricks Lakehouse Platform.
• Architect scalable, secure, and high-performance data platforms across AWS, Azure, and/or GCP.
• Define end-to-end solution architecture aligned with business and technical objectives.
• Lead end-to-end enterprise Databricks implementations from discovery through production deployment.
• Deliver large-scale production workloads with focus on scalability, reliability, and performance.
• Solve complex challenges involving distributed data processing, platform optimization, and cloud-native architectures.
• Develop and optimize enterprise data pipelines using Apache Spark and Databricks.
• Build scalable ETL/ELT frameworks using Delta Lake and modern data engineering practices.
• Drive platform performance tuning, cost optimization, and workload scalability.
• Design and implement cloud-native data solutions across AWS, Azure, and GCP.
• Collaborate with platform engineering teams on CI/CD pipelines, deployment automation, Infrastructure-as-Code, and DevOps practices.
• Support enterprise MLOps implementation and integration with modern AI workflows.
• Lead architecture workshops, technical discovery sessions, and executive presentations.
• Partner with customers to understand business challenges and translate them into scalable technical solutions.
• Provide technical leadership throughout implementation and post-production support.
• Define enterprise architecture standards, implementation best practices, governance frameworks, and reusable solution accelerators.
• Ensure security, compliance, data quality, and operational excellence across implementations.
• Mentor engineering teams and contribute to organizational capability building.

Key Requirements

• 10+ years of consulting and technology experience.
• Minimum 7+ years of experience in Data Engineering, Data Platforms, or Analytics.
• Minimum 6-8 enterprise Databricks implementations delivered in production environments.
• Hands-on enterprise delivery experience is mandatory.
• Strong experience designing and deploying large-scale distributed data platforms.
• Strong customer-facing consulting and solution architecture experience.
• Experience working with global enterprise customers across multiple industries.
• Strong expertise in Apache Spark, Databricks, Delta Lake, and modern data engineering practices.
• Experience with AWS, Azure, and/or GCP.
• Bachelor's degree in Computer Science, Engineering, Information Technology, or related discipline.
• Master's degree preferred.
• Databricks Data Engineer Professional Certification - Mandatory.
• Additional AWS, Azure, or GCP certifications are highly desirable.
• Excellent technical, communication, and presentation skills.
• Strong consulting and problem-solving mindset.
• Executive presence and stakeholder management capabilities.
• Strong customer engagement and workshop facilitation skills.
• Ability to influence technical and business decision-makers.