Senior Data Architect: Databricks & Data Solutions

Genworth; Richmond (VA); Hybrid; USD 121,000 - 187,000; Full time

Benefits offered by this job

Competitive compensation

Comprehensive healthcare coverage

401(k) with employer contributions

Generous paid time off and holidays

Tuition reimbursement & training

Job summary

Genworth is seeking a Lead Solution Architect for Databricks to influence and communicate architecture decisions across data projects. You will act as a change agent to promote data architecture adoption, design reusable frameworks, and mentor teams on best practices.

The role requires hands-on experience with Databricks, Spark, and Kafka, plus strong collaboration with business stakeholders, data engineers, and cloud teams. A four-year degree and relevant certifications are preferred.

Qualifications

• 5+ years experience as a data architect or related roles.
• Hands-on experience with Databricks, Spark, Kafka and data pipelines.
• Masters or certifications relevant to the position preferred.
• Ability to lead architecture patterns and provide design guidance.

Responsibilities

• Evaluate project scope, timelines, trade-offs, costs, and value.
• Translate requirements into architectures aligned to reference architecture.
• Define phased implementation approaches delivering early value.
• Guide data engineering teams on design, build and test.
• Lead or support proofs of concept to validate patterns.
• Participate in SDLC to implement designs and meet requirements.
• Establish reusable design patterns across projects.

Skills

Databricks

Spark

Kafka

Data modeling

CI/CD

Cloud services

Education

Bachelor's degree

Masters preferred

Tools

Databricks

Spark

Kafka

Ingestion tools

Lakehouse

Job description

Genworth is seeking a Lead Solution Architect for Databricks to influence and communicate architecture decisions across data projects. You will act as a change agent to promote data architecture adoption, design reusable frameworks, and mentor teams on best practices.

The role requires hands-on experience with Databricks, Spark, and Kafka, plus strong collaboration with business stakeholders, data engineers, and cloud teams. A four-year degree and relevant certifications are preferred.