Data & Analytics Solutions Architect

On-site
Posted Oct 10, 2026
1 position

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Employment type: Full-time
Experience level: Lead · 14+ years
Minimum education: Bachelor’s degree
Posting language: English
Working hours: 40 hours per week
Seniority: Associate
Application method: Direct apply is available

Job summary

Design end-to-end AWS and Databricks data and AI architectures, including scalable Lakehouse platforms, ingestion pipelines, and analytics solutions. Lead governance, security, modernization, migration, optimization, and architecture standards while collaborating with stakeholders, supporting client engagements, and mentoring engineers.

Job details

We are hiring for a Data & Analytics Solutions Architect AWS & Databricks This role focuses on designing enterprise data platforms, Lakehouse architectures, and AI-driven analytics solutions on AWS. The ideal candidate has 14+ years of experience in data architecture, Databricks, data engineering, and cloud modernization. What You Bring 14+ years of experience in Enterprise Data Architecture, AWS, Databricks, and Cloud Modernization Strong expertise in AWS Data Services, Databricks Genie, Unity Catalog, Delta Lake, Python, PySpark, and SQL Experience designing Lakehouse architectures and enterprise data platforms Knowledge of Databricks SQL, Workflows, Lakeflow, MLflow, and performance optimization Experience with ETL/ELT, batch and streaming pipelines, APIs, and DataOps Knowledge of data governance, security, compliance, and responsible AI Experience with HLD/LLD, migration planning, architecture reviews, and technical governance Understanding of BFSI regulatory and compliance requirements Bachelor's degree in Computer Science, Engineering, Information Systems, Data Management, or a related discipline What You'll Do Design end-to-end AWS and Databricks data and AI architectures Build scalable Lakehouse, data ingestion, and analytics solutions Develop AI-driven analytics using Databricks Genie and semantic models Establish data governance, security, and observability standards Lead cloud modernization, migration, and platform optimization Drive architecture reviews, technical standards, and DataOps practices Collaborate with engineering teams and stakeholders on solution delivery Support technical presentations, effort estimation, and client workshops Mentor engineers and develop reusable architecture frameworks Nice to have Certifications in AWS, Databricks, Data Engineering, Enterprise Architecture, Security, or AI/ML

What you’ll do

Requirements

Requires 14+ years of experience in enterprise data architecture, AWS, Databricks, and cloud modernization, with strong expertise in AWS data services, Databricks tools, Python, PySpark, and SQL. Candidates should have experience with Lakehouse design, data pipelines, governance, security, compliance, architecture reviews, and BFSI requirements, plus a bachelor's degree in a related discipline.