Databricks Resident Data Architect

Description

We are seeking an experienced Resident Data Architect with deep expertise in the Databricks Lakehouse Platform to lead architecture, delivery, and adoption initiatives for enterprise data and analytics programs. This role will serve as the trusted advisor to the customer, ensuring successful implementation, optimization, and governance of modern data platforms while driving business value through scalable data solutions.
Key Responsibilities

- Act as the on-site or dedicated Databricks Resident Architect supporting strategic customer initiatives.

- Lead architecture, design, and delivery of enterprise-scale data platforms leveraging Databricks.

- Partner with business stakeholders, technical teams, and leadership to define data strategies and roadmaps.

- Design and implement scalable data lakehouse architectures.

- Drive data modernization, migration, and cloud transformation initiatives.

- Establish best practices for data engineering, governance, security, and performance optimization.

- Guide development teams on data modeling, ETL/ELT, and modern analytics architectures.

- Ensure successful project delivery, risk management, and stakeholder communication.

- Provide technical leadership and mentorship to customer and partner teams.

- Support adoption of AI/ML, real-time analytics, and advanced data capabilities within Databricks.

- Collaborate with executive leadership to align technical solutions with business objectives.

Required Qualifications

- 7+ years of experience in data engineering, analytics, and modern data platforms, with 10+ years in consulting and client-facing engagements.

- Databricks Certified Data Engineer Professional certification (or equivalent advanced certification) required.

- Proven track record delivering 6–8+ Databricks implementations with hands-on development experience.

- Strong expertise in at least one major cloud platform (AWS, Azure, or GCP) and working knowledge of multiple cloud ecosystems.

- Deep experience with Apache Spark, including distributed computing concepts and Spark runtime internals.

- Experience implementing and supporting CI/CD pipelines for production deployments.

- Solid understanding of MLOps principles, tools, and best practices.

- Current knowledge of the Databricks platform, products, and evolving feature set.

- Demonstrated ability to optimize performance, scalability, and reliability across data workloads and architectures.

- Strong communication and stakeholder management skills, with the ability to translate business requirements into scalable technical solutions.

Preferred Qualifications

- Databricks Certified Data Engineer, Architect, or related certifications.

- Experience with AI/ML implementation and MLOps.

- Knowledge of Unity Catalog, Data Governance, and Data Quality frameworks.

- Experience with Power BI, Tableau, or other data visualization platforms.

- Previous experience in professional services, consulting, or managed service delivery organizations.

Key Skills

- Databricks

- Data Architecture

- Data Engineering

- Service Delivery

- Cloud Architecture (Azure/AWS/GCP)

- Apache Spark

- Delta Lake

- Data Governance

- Data Integration

- Lakehouse Architecture

- Stakeholder Management

- Digital Transformation

- Technical Leadership

- Enterprise Consulting

Success Profile

The ideal candidate combines hands-on Databricks architecture expertise with strong service delivery and customer-facing consulting skills , acting as both a trusted advisor and technical leader to drive successful enterprise data modernization initiatives.

Matrix is a global, dynamic, fast-growing technical consultancy leading technology services company with 13000 employees worldwide. Since its foundation in 2001, Matrix has made more travelers and acquisitions and has executed some of the largest, most significant. The company specializes in implementing and developing leading technologies, software solutions, and products. I