Senior Data Technology Consultant, Databricks Data & AI Practice

EPAM Systems; United States; Remote; USD 180,000 - 260,000; Full time

Job summary

EPAM Systems Inc. seeks a seasoned Senior Data Technology Consultant to own end-to-end Databricks initiatives in the United States.

You will design Lakehouse architectures, lead pre-sales engagements, and drive production deployments with a hands-on leadership approach. Responsibilities include architecting solutions, guiding discovery sessions, and delivering compelling proposals with strong commercial acumen.

Qualifications

• Databricks platform expertise across Spark, Delta Lake, Unity Catalog, and ML tooling.
• Experience leading complex, enterprise Databricks implementations and migrations.
• Strong ability to translate Lakehouse/AI concepts for senior stakeholders.
• Proven ability to create proposals, RFP responses, and pricing models for Databricks services.

Responsibilities

• Architect Databricks solutions: design Lakehouse architectures and AI solutions; integrate with cloud and partner tech.
• Lead the presales lifecycle: solution design, scoping, and effort estimation for Databricks engagements.
• Facilitate discovery: run client workshops to capture objectives and define target-state architecture.
• Drive commercial success: craft proposals, pricing, and engagement models with account teams.
• Lead delivery: guide teams from advisory through production, applying best practices in security, FinOps, CI/CD, and MLOps/LLMOps.

Skills

Databricks Expertise

Cloud & Ecosystem

Presales Background

Communication & Storytelling

Commercial & Proposal Acumen

Strategic Advisory Skills

Databricks Certifications

Tools

dbt

Fivetran

Power BI

Tableau

Terraform

Job description

We are looking for seasoned Senior Data Technology Consultants to join our Databricks Data & AI Consulting Practice. You will own end-to-end Databricks initiatives. In pre-sales, you will design the Lakehouse and AI solution. After the win, you will lead strategic client engagements from advisory through production. This is a hands-on leadership role for technologists who combine deep Databricks expertise with commercial ownership and client impact.

Req.#1128476334

Responsibilities

• Architect Databricks Solutions: Design Lakehouse architectures and AI solutions on Databricks. This covers Delta Lake, Unity Catalog governance, Lakeflow/Delta Live Tables pipelines, Databricks SQL, and Mosaic AI (ML, GenAI, agents, Model Serving). Where needed, integrate with cloud services and partner technologies
• Lead the Presales Lifecycle: Own opportunity solution design, technical scoping, and effort estimation for Databricks engagements, including migrations to Databricks, platform builds, and AI/ML use cases
• Facilitate Discovery: Run client workshops to capture business objectives, assess current-state data platforms, and define the target-state architecture and Databricks adoption path
• Drive Commercial Success: Craft proposals, pricing and engagement models, and value propositions. Work with Databricks account teams to win and expand engagements
• Lead Delivery: Guide teams from advisory through production, applying Databricks best practices for performance, cost optimization (FinOps), security, CI/CD, and MLOps/LLMOps

Requirements

• Databricks Expertise: Deep, hands-on experience across the Databricks platform. This includes Spark, Delta Lake, Unity Catalog, Workflows, Lakeflow/DLT, Databricks SQL, and Mosaic AI/MLflow. You should have a track record of leading complex, enterprise-scale Databricks implementations, such as platform builds, data migrations, and ML/GenAI production deployments
• Cloud & Ecosystem: Strong working knowledge of at least one major cloud (AWS, Azure, or GCP) and of the partner technologies commonly used with Databricks, such as dbt, Fivetran, Power BI/Tableau, and Terraform
• Consulting & Presales Background: Substantial experience in presales, solution architecture, or consulting centered on Databricks and data/AI use cases
• Communication & Storytelling: Outstanding ability to translate complex Lakehouse and AI concepts into clear, client-friendly narratives for senior stakeholders
• Commercial & Proposal Acumen: Proven ability to produce detailed proposals, RFP responses, and pricing and engagement models for Databricks-based services
• Strategic Advisory Skills: Strong grasp of consulting principles, with the ability to define future-state recommendations, roadmaps, and project scopes in fast-paced settings
• Must have: Databricks certifications (e.g., Data Engineer Professional, Machine Learning Professional, or Generative AI Engineer) and experience with Databricks partner programs