Databricks Architect

Job Title: Databricks Architect with strong Data Fabric experience

Experience: 11+ Years
Work Mode: Remote

Employment Type: Contract 

WORK AUTHORIZATION: CANDIDATES MUST BE AUTHORIZED TO WORK IN THE UNITED STATES WITHOUT CURRENT OR FUTURE SPONSORSHIP. 

We are seeking an experienced Databricks Architect with strong Data Fabric experience to design and lead enterprise-scale modern data platforms. The ideal candidate will have deep expertise in Databricks, Azure/AWS cloud data platforms, Data Fabric architecture, data engineering, data governance, and enterprise data integration.

Responsibilities:

• Define data architecture strategy.
• Design scalable and secure data platforms.
• Enable seamless access to data across multiple domains, applications, and cloud environments.

Required Technical Skills:

• 10+ years of experience in Data Architecture / Data Engineering / Solution Architecture
• Strong hands-on architecture experience with Databricks
• Strong understanding of Data Fabric architecture and principles
• Expertise in Databricks Lakehouse, Delta Lake, Unity Catalogue, Spark, and PySpark
• Strong experience with Azure or AWS data services
• Experience designing enterprise-scale data pipelines and data integration frameworks.
• Strong knowledge of ETL/ELT, batch processing, streaming, and real-time data architectures
• Experience with data governance, metadata, data lineage, data quality, and data security.
• Strong SQL and Python skills
• Experience with Kafka or equivalent streaming technologies.
• Experience with data warehousing technologies such as Snowflake, Azure Synapse, Teradata, or similar.
• Knowledge of API-based integration and microservices architecture
• Experience with CI/CD, DevOps, Infrastructure as Code, and automated deployment processes.

Data Fabric Expertise:

• Enterprise Data Fabric architecture
• Data Mesh and Data Fabric concepts
• Domain-oriented data architecture
• Data products
• Metadata-driven architecture
• Data catalogue and discovery
• Data lineage and observability
• Master Data Management (MDM)
• Data governance and stewardship
• Data quality and data lifecycle management
• Federated data access and integration
• Self-service analytics
• Secure data sharing across business domains
• Integration of cloud, on-premises, and SaaS data sources

Preferred / Nice-to-Have:

• Databricks certifications such as Databricks Certified Data Engineer / Data Architect
• Experience with Microsoft Purview, Collibra, Alation, Informatica, or similar data governance/catalogue platforms.
• Experience with Azure Data Factory / Fabric, AWS Glue, or equivalent.
• Knowledge of Snowflake and modern cloud data warehouse architectures
• Experience implementing enterprise data platforms for Financial Services, Healthcare, Retail, Manufacturing, or Telecom
• Experience with GenAI/ML data platforms and AI-ready data architectures.