Databricks Architect

Wissen Infotech

United States

1 day ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

10 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Artificial Intelligence Amazon Web Services Business Analytics Applications Microsoft Azure Batch Processing Software as a Service Continuous Integration Data Architecture Information Engineering Data Governance Data Infrastructure Data Integration

+33 more

Extract Transform Load (ETL) Data Security Data Warehousing DevOps Information Lifecycle Management Python (Programming Language) Metadata Standard Sql Data Streaming Teradata SQL Enterprise Data Management Cloud Platform System Azure Data Factory Snowflake Apache Spark Microsoft Fabric Data Lakes Pyspark Infrastructure Automation Frameworks Data Lineage Collibra Deployment Automation AWS Glue AWS Data Analytics Real Time Data Apache Kafka Data Management Video Streaming Api Design Azure Synapse Analytics Data Pipelines Databricks Microservices

Job description

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

Requirements

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., * 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.