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Senior Data Technology Consultant, Databricks Data & AI Practice

EPAM SystemsNew York, NY🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationNew York, NY, United States
SQLAWSMLOpsMLflowTableauDatabricksGoogle CloudTerraformUnitydbtGenerative AIAzureMachine LearningPower BICI/CDDelta Lake

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.# 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 Google Cloud Platform) 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

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