RedBeard Solutions
Resident Solutions Architect (Databricks)
Fully remote (US) Resident Solutions Architect delivering hands-on Databricks professional-services engagements for clients: designing architectures, writing Python/Scala, tuning Spark, and supporting production data/AI deployments across AWS, Azure, and GCP. Hourly contract pay: $80-90/hr W2 or $95-105 C2C.
- Compensation
- $80–$105 / hr
- Location
- Not listed
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 7+ years
- Category
- Architecture
- Posted
Skills
Must have
- 10+ years of consulting experience
- 7+ years experience in data engineering, data platforms & analytics
- Completed Data Engineering Professional certification & required classes
- Minimum 6-8+ projects delivered with hands-on development experience on Databricks
- Working knowledge of two or more cloud ecosystems (AWS, Azure, GCP) with deep expertise in at least one
- Deep experience with distributed computing with Spark, including Spark runtime internals
- Strong coding ability in Python or Scala
- Familiarity with CI/CD for production deployments
- Working knowledge of MLOps
- Current knowledge across the breadth of Databricks product and platform features
- Familiarity with optimizations for performance and scalability
- Good client-facing / consulting / customer engagement skills
Nice to have
- Familiarity with multiple cloud providers
- Knowledge of production deployments: CI/CD, MLOps, data architectures
Full description
Job Title: Resident Solutions Architect (Databricks)Location: Fully Remote (in the US) *Some travel depending on end client needs/projectsNumber of openings: Many
Experience: 10+ years
Salary: $80-90/hr W2 or $95-105 C2C
Start Date: Open roles, 2-4 week process (faster for strong candidates!
Job Description:
Core Responsibilities
Some of the major responsibilities for an RSA are:
- Engage with customers on short- to mid-term professional services projects using the Databricks platform (data engineering, data science, cloud).
- Design and build reference architectures, help with production-level use cases and deployments of big data / AI applications.
- Collaborate with engagement/project managers, customer teams, and internal engineering/support teams to ensure technical delivery meets customer needs
- Provide escalated technical support or operational assistance for customer engagements, helping to resolve issues or unblock customers
- Work hands-on: write code (e.g., Python, Scala), work with distributed compute (Apache Spark), integrate across cloud ecosystems.
- Possibly scope new engagements, support sales or pre-sales (depending on region/team) by estimating effort, defining deliverables.
- Provide feedback to product/engineering from customer engagements (help improve platform, features
Required Skills & Qualifications
an RSA typically needs:
- Several years (often 8+ years) in data engineering, analytics, platform roles.
- Strong coding ability in Python or Scala, and comfortable with distributed processing (Spark).
- Experience working across at least one cloud provider (AWS, Azure, GCP) and preferably familiarity with multiple.
- Knowledge of production deployments: CI/CD, MLOps, data architectures.
- Good client-facing / consulting / customer engagement skills (communicating technical ideas, scoping projects, working with customer teams).
- What You Should Expect from the Role
- It's billable professional services: you'll often be working as a consultant/embedded engineer with customers, delivering real implementations rather than purely strategy.
- The role is technically deep: you'll not only design solutions but often build them, debug issues, optimize performance.
Because it is delivery-oriented, you may deal with customer escalations and operational issues, not just green-field new builds.