Lead Solutions Architect

Role Overview

• Architect and design enterprise-grade cloud solutions leveraging AWS services (EC2, S3, Glue, Lambda, Kinesis, IAM, Redshift, EMR).
• Design Databricks Lakehouse solutions including Delta Lake, Unity Catalog, Spark optimization, governance, and MLOps patterns.
• Build scalable ETL/ELT pipelines, real-time streaming architectures, and reusable data integration frameworks.
• Develop high-level and low-level architecture blueprints ensuring security, compliance, cost efficiency, reliability, and performance.
• (Preferred) Architect cloud/on-prem hybrid data platforms using Azure services such as Azure Data Lake, ADF, Azure Databricks, Synapse, etc.
• Lead requirement discovery, translate business needs into robust architectural designs and roadmaps.
• Create HLDs, LLDs, data flow diagrams, integration patterns, deployment models, and security reference architectures.
• Oversee end-to-end delivery, guiding engineering and DevOps teams through implementation and optimization.
• Perform architecture assessments and recommend improvements for scalability, resilience, and cost savings.
• Provide thought leadership and hands-on direction to data engineering, analytics, DevOps, and platform teams.
• Establish best practices for coding, data governance, CI/CD, infrastructure automation, and environment management.
• Introduce and evaluate emerging cloud technologies, tools, and frameworks relevant to analytics and modern data platforms.
• Act as technical SME for client conversations, workshops, and executive presentations.
• Communicate complex architectural concepts clearly to both technical and non-technical audiences.
• Partner closely with business stakeholders to define solution vision, roadmap, and success metrics.

Requirements

• 12–15 years of overall IT experience with strong focus on cloud, data engineering, and enterprise architecture.
• 5+ years of hands-on experience architecting production solutions on AWS.
• 3+ years’ strong experience in Databricks (Spark, Delta Lake, MLflow, Unity Catalog).
• Proficiency in Python, SQL, PySpark, and distributed data processing frameworks.
• Deep understanding of data modeling, data governance, metadata management, and modern security practices.
• Experience with CI/CD pipelines, Terraform / CloudFormation, GitOps, and end-to-end automation.
• Strong knowledge of cloud networking, VPCs, IAM, encryption, identity governance, and security frameworks (NIST, CIS benchmarks).
• (Preferred) Experience with Azure cloud architecture, including Azure Databricks, ADF, ADLS, Synapse, and Azure DevOps.

Tech Stack

• Amazon Redshift
• AWS
• Azure
• Cloud
• EC2
• ETL
• PySpark
• Python
• Spark
• SQL
• Terraform
• Unity

Benefits

• Health insurance
• Retirement plans
• Paid time off