Databricks Architect

TechDoQuest; Edison (NJ); Remote; USD 130,000 - 180,000; Full time

Job summary

A leading tech company in the United States is seeking an experienced Data Solutions Architect to lead cloud-native data solutions. Responsibilities include developing modern architecture, collaborating with clients, and building smart operational frameworks for DataOps and MLOps. The ideal candidate has over 14 years of experience, with expertise in Databricks, Azure, and data governance. This role offers a dynamic environment focused on performance and scalability.

Qualifications

• 14+ years of experience with 4 years in Cloud native Data Solutions.
• Experience in Databricks, Azure, and data governance.
• Strong knowledge of data warehousing and cloud-native databases.

Responsibilities

• Develop modern data solutions for cloud-native platforms.
• Build infrastructure in Databricks and orchestrate workflows.
• Collaborate with customers for data modernization.

Skills

Cloud-native data solutions

Databricks

Data processing frameworks

Agile/Scrum methodologies

ETL Tools

Job description

Responsibilities

• Develop modern data solutions and architecture for cloud-native data platforms.
• Build cost-effective infrastructure in Databricks and orchestrate workflows using Databricks/ADF.
• Lead data strategy sessions focused on scalability, performance, and flexibility.
• Collaborate with customers to implement solutions for data modernization.
• Create training plans and learning materials to upskill VM associates.
• Build a smart operations framework for DataOps and MLOps.

Requirements

• Should have 14+ years of experience with last 4 years in implementing Cloud native end-to-end Data Solutions in Databricks from ingestion to consumption to support variety of needs such as Modern Data warehouse, BI, Insights and Analytics
• Experience in architecture and implementing End to End Modern Data Solutions using Azure and advanced data processing frameworks like Databricks
• Experience with Databricks, PySpark, and modern data platforms.
• Proficiency in cloud-native architecture and data governance.
• Strong experience in migrating from on-premises to cloud solutions (Spark, Hadoop to Databricks).
• Understanding of Agile/Scrum methodologies.
• Demonstrated knowledge of data warehouse concepts. Strong understanding of cloud-native databases, columnar database architectures.
• Ability to work with Data Engineering teams, Data Management Team, BI and Analytics in a complex development IT environment.
• Good appreciation and at least one implementation experience on processing substrates in Data Engineering - such as ETL Tools, Kafka, ELT techniques
• Data Mesh and Data Products designing, and implementation knowledge will be an added advantage.