Data Solutions Architect

Job Summary

We are seeking an experienced Data Solutions Architect to design and implement scalable, secure, and cloud-native data platforms with expertise in data warehousing, lakehouse architectures, and multi-tenant environments. The ideal candidate will define enterprise data architecture, enable advanced analytics and AI/ML, and translate business requirements into robust technical solutions.

Key Responsibilities

Architecture & Design

• Design end-to-end cloud data platform architecture across ingestion, storage, transformation, and consumption.
• Develop scalable Lakehouse, Data Warehouse, and Data Mesh solutions.
• Establish reference architectures and reusable design patterns.

Multi-Tenant Platform

• Design secure multi-tenant data platforms with tenant isolation and lifecycle management.
• Implement policy-based access control, encryption, and compliance frameworks.

Cloud Data Platform

• Architect enterprise data warehouse and lakehouse solutions.
• Design batch and real-time data pipelines.
• Optimize data models, query performance, and platform scalability.

Data Governance & Security

• Define data governance, cataloging, lineage, and metadata management.
• Implement enterprise security, identity integration, and regulatory compliance.

Integration & Performance

• Design integrations with APIs, streaming platforms, and enterprise systems.
• Ensure high availability, scalability, reliability, and cost optimization.

Leadership & Innovation

• Collaborate with business and technology stakeholders to deliver architecture roadmaps.
• Mentor engineering teams and promote architecture best practices.
• Drive adoption of AI/ML and GenAI capabilities within the data platform.

Required Qualifications / Skills

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 10+ years of experience in Data Engineering/Data Architecture.
• Strong experience in enterprise cloud data platforms, multi-tenant solutions, and modern data architectures.
• Excellent stakeholder management, leadership, and communication skills.
• Cloud Platforms: AWS, Azure, or GCP
• Data Platforms: Snowflake, Databricks, Microsoft Fabric, Synapse, Redshift, BigQuery
• Technologies: Spark, Kafka, SQL, Python, ETL/ELT, Delta Lake
• Expertise in Lakehouse, Data Warehouse, Multi-Tenant Architecture, Data Governance, Security, and Cloud Data Engineering