Databricks Lakehouse Architect & Platform Lead

MACHINE LEARNING TECHNOLOGIES LLC; Boston (MA); Presencial; USD 180 000 - 260 000; Tempo integral

Resumo da oferta

MACHINE LEARNING TECHNOLOGIES LLC in Boston, MA is seeking an experienced Databricks Integration Engineer to design and deliver scalable data and AI platforms on the Databricks Lakehouse. You will define the target architecture, establish engineering standards, and guide ingestion, governance, and production operations.

The role requires 12–15 years in data engineering or cloud architecture, with hands-on Databricks, Spark, Delta Lake, SQL, and Python.

Qualificações

• 12–15 years of data engineering or cloud architecture experience.
• Hands-on Databricks expertise and cloud platform knowledge.
• Strong knowledge of Spark, Delta Lake, Unity Catalog, SQL and Python.
• Experience designing enterprise-scale data and AI platforms with governance.

Responsabilidades

• Design scalable and secure Databricks Lakehouse architectures.
• Define target architecture, engineering standards, and reusable frameworks.
• Lead data ingestion, transformation, governance, and production operations.
• Conduct architecture reviews and technology evaluations.
• Drive performance and cost optimization across the platform.
• Establish CI/CD, monitoring, and operational best practices.
• Partner with client stakeholders, data engineers, analysts, security teams, and vendors to translate business requirements into technical solutions.
• Provide technical leadership and mentoring to engineering teams.

Conhecimentos

Databricks

Cloud architecture

Apache Spark

Delta Lake

Unity Catalog

SQL

Python

CI/CD

Security best practices

Stakeholder management

Descrição da oferta de emprego

MACHINE LEARNING TECHNOLOGIES LLC in Boston, MA is seeking an experienced Databricks Integration Engineer to design and deliver scalable data and AI platforms on the Databricks Lakehouse. You will define the target architecture, establish engineering standards, and guide ingestion, governance, and production operations.

The role requires 12–15 years in data engineering or cloud architecture, with hands-on Databricks, Spark, Delta Lake, SQL, and Python.