Technical Architect

Gemini Solutions Pvt Ltd; Irvine (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Gemini Solutions Pvt Ltd. seeks a Technical Architect – Data Engineering & Databricks to design and lead scalable cloud data platforms. You will work directly with clients and mentor offshore engineering teams, delivering end-to-end Databricks Lakehouse solutions.

The role requires hands-on Databricks, strong Python/SQL skills, and experience with AWS or Azure, Delta Lake, and data governance. You will shape architecture decisions focusing on scalability, security, and cost optimization.

Qualifications

• 10–15 years of experience in Data Engineering, Data Architecture, or Solution Architecture.
• Strong hands-on experience with Databricks and modern data engineering platforms.
• Proficiency in Python, SQL, and PySpark/Spark.
• Experience with AWS and/or Azure; Delta Lake and Unity Catalog knowledge.

Responsibilities

• Own the end-to-end architecture and technical design of modern data platforms using Databricks and AWS/Azure.
• Design scalable data ingestion, processing, transformation, and consumption architectures.
• Architect and implement Databricks Lakehouse solutions, including Bronze/Silver/Gold, Delta Lake, Unity Catalog, and data governance.
• Design and implement Data Quality & Assurance, validation, monitoring, and observability frameworks.
• Work with client stakeholders and offshore teams to understand requirements and drive technical delivery.

Skills

Databricks

Python

SQL

PySpark

AWS/Azure

Data Architecture

CI/CD/DevOps

Data Governance

Airflow

Client-facing leadership

Job description

Role OverviewWe are looking for a Technical Architect – Data Engineering & Databricks to designand lead modern, scalable cloud data platforms. The ideal candidate will have stronghands-on Databricks experience, solid architecture and system-design skills, and theability to work directly with clients while providing technical leadership to offshoreengineering teams.

Responsibilities

• Own the end-to-end architecture and technical design of modern data platforms using Databricks and AWS/Azure.
• Design scalable data ingestion, processing, transformation, and consumption architectures.
• Architect and implement Databricks Lakehouse solutions, including source ingestion, Medallion Architecture (Bronze/Silver/Gold), Delta Lake, Unity Catalog, and data governance.
• Design and implement Data Quality & Assurance (DQA), validation, monitoring, and observability frameworks.
• Work directly with client stakeholders and offshore technical teams to understand requirements, define solutions, and drive technical delivery.
• Act as the technical bridge between the client and offshore team, providing technical direction, conducting design reviews, and resolving complex technical challenges.
• Drive architecture decisions around scalability, performance, security, reliability, and cost optimization.
• Establish and promote CI/CD, DevOps, and Infrastructure-as-Code best practices.
• Provide technical leadership, mentoring, and guidance to Data Engineering teams.
• Evaluate and adopt relevant Databricks capabilities and emerging technologies, including AI-enabled data solutions.

Required Skills

• 10–15 years of experience in Data Engineering, Data Architecture, or SolutionArchitecture.
• Strong hands-on experience with Databricks and modern data engineeringplatforms.
• Strong proficiency in Python, SQL, and PySpark/Spark.
• Strong experience with AWS and/or Azure.
• Strong understanding of Delta Lake and Unity Catalog.
• Experience implementing data quality, governance, security, lineage, andobservability.
• Experience with Airflow, Dagster, or equivalent workflow orchestration tools.
• Strong system design and architecture capabilities.
• Experience with Git, CI/CD, and DevOps practices.
• Excellent client-facing communication, stakeholder management, andtechnical leadership skills.

Preferred Skills

• Databricks Certified Data Engineer Professional certification.
• Experience building and implementing Databricks platforms from theground up.
• Experience with dbt and modern ELT patterns.
• Experience with Terraform and/or Databricks Asset Bundles (DABs).
• Experience with on-premises to cloud migration and modernization.
• Experience with streaming or event-driven architectures.
• Exposure to Agent Bricks and AI-enabled data solutions.
• Experience working with enterprise-scale or multi-domain data platforms.