Lead Databricks Consultant- Strategic Solution Architecture

Title: Lead Databricks Consultant - Strategic Solution Architecture

Location: Remote

Only W2 ()

Rate $80-100/hr on W2/1099

Mandatory : Presales and solutioning

Health Care Domain



Key responsibilities : Lead Databricks Consultant - Strategic Solution Architecture

Presales and solutioning

Partner with sales and account teams to run discovery sessions, understand customer objectives, and identify high value Databricks use cases.

Shape solution visions and reference architectures for data, analytics, and AI platforms built on Databricks and cloud services (Azure, AWS, or Google Cloud Platform).

Develop proposals and statements of work, including scope, phases, estimates, risks, and assumptions for Databricks engagements.

Deliver technical presentations, whiteboard sessions, and demos that clearly communicate Databricks capabilities and business value to diverse audiences.

Address technical objections, guide architecture discussions, and build confidence with client architects and executives during the sales cycle.

Drive additional revenue by proactively uncovering opportunities to expand business within current customer base

Architecture and delivery leadership

Lead the design and implementation of secure, scalable Databricks Lakehouse architectures, including Delta Lake, Unity Catalog, and integration with upstream and downstream systems.

Pro-actively define offerings, IP and associated collateral that will resonate with both new/existing customers and help close new business

Oversee the build of batch and streaming data pipelines, notebooks, and Databricks SQL assets using Spark, Python, and SQL, following medallion and other best practice patterns.

Define and enforce engineering standards, including code quality, testing, CI/CD, observability, and operational readiness for Databricks workloads.

Collaborate with project managers and client stakeholders to plan releases, manage dependencies, mitigate risks, and ensure on time, on budget delivery.

Provide hands on technical leadership to data engineers and analysts, reviewing designs and code, and unblocking complex technical issues.

Governance, operations, and adoption

Implement data governance and security practices using Unity Catalog and related tools, including access control, lineage, and compliance aligned policies.

Optimize performance, reliability, and cost of Databricks workloads through cluster tuning, storage strategies, and monitoring.

Drive change management and enablement by creating documentation, runbooks, and training materials, and facilitating knowledge transfer to client teams.

Support production go lives and post olive stabilization, ensuring robust handover to client operations or managed services teams.

Work with specialty sales team and COE Lead to create a plan to engage with and add net new customers to existing portfolio

Required qualifications

Excellent communication, stakeholder management, and presentation skills, with the ability to influence technical and nontechnical audiences.

Demonstrated ability to run workshops, gather requirements, and translate business needs into technical designs and phased roadmaps.

Proven experience leading client facing data or analytics projects in a consulting, professional services, or similar environment.

Extensive hands-on experience designing and delivering data platforms and pipelines on Databricks, including Delta Lake, Jobs/Workflows, and Databricks SQL.

Strong programming skills in at least two of: Python, PySpark, and SQL, with demonstrated ability to build performant batch and streaming solutions.

Solid understanding of cloud services (Azure, AWS, or Google Cloud Platform) relevant to Databricks deployments, such as storage, networking, identity, and DevOps tooling.

Experience implementing data governance, security, and access control in Lakehouse or data platform environments using Unity Catalog or similar tools.

Preferred qualifications


Experience with largescale data platform migrations or modernizations (e.g., from legacy ETL/warehouse tools to Databricks).