ExecutivePlacements.com · 1 week ago
Urgent to Fill-RSA DataBricks-Remote
United States
Full-time
Remote
Senior Level, Lead/Staff
8+ years expExecutivePlacements.com is seeking a professional with extensive experience in data engineering and analytics to engage with customers on projects using the Databricks platform. The role involves designing and building reference architectures, providing technical support, and working hands-on with coding and distributed computing to deliver solutions that meet customer needs.
Human ResourcesOnline PortalsRecruiting
Responsibilities
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)
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
You'll need adaptability: customers across industries, various workloads (ETL, streaming, AI/ML), different cloud platforms
The role also helps the customer adopt Databricks, so you're enabling change in how they think about data/AI, not just delivering code
Be a trusted advisor with authority and clarity
Set expectations and simplify complex ideas
Earn trust early, even before delivering technical work
Align with the customer, listen actively, and empathize with their concerns
Always under-promise and over-deliver
Focus on solving problems to build trust and unlock future work
Use clear, jargon-free communication
Identify stakeholders, understand drivers of change, and mitigate risks
Offer quick-win alternatives to free up customer bandwidth for strategic tasks
Assess if building aligns with the company's core competencies or adds technical debt
Highlight Databricks' value proposition in scalability and maintainability
Empathize-custom solutions are often someone's "baby."
Offer bake-offs to demonstrate Databricks' strengths
Educate the customer-understand the specifics: data size, current framework, future scaling needs
Clarify if Spark is truly the bottleneck
Offer bake-offs on speed, performance, and cost
Build a clear, phased migration plan with deliverables
Coordinate with the account team to align messaging and reinforce trust
Determine if missing features are true blockers
Educate the account team on PUPR (Public Preview) vs. GA (General Availability)
If necessary, build lightweight custom solutions to bridge gaps
Re-align customer expectations with reality and roadmap
Qualification
Required
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)
7+ years experience in data eng, data platforms & analytics
10+ years of consulting experience
Completed Data Engineering Professional certification & required classes
Minimum 6-8+ projects delivered with hands-on experience in development on databricks
Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with deep expertise in at least one
Deep experience with distributed computing with Spark with knowledge of Spark runtime internals
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
Company
ExecutivePlacements.com
Online recruitment
11-50 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase