EPAM Systems

About the Role

We are seeking an experienced Senior Data Technology Consultant to join our growing Data & AI practice. This role bridges technology with business value, helping clients harness the power of data to drive transformative business results. You will play a pivotal role in crafting innovative data solutions, supporting sales efforts, and delivering exceptional value to our clients through strategic consulting and technical expertise.

Key Responsibilities

• Work closely with sales, delivery, and expert teams to align client needs with data-driven solutions, effectively connecting business challenges to our offerings
• Own the end-to-end presales process, including opportunity qualification, solution design, proposal development, demos, and client presentations
• Lead workshops and meetings with clients to gather business objectives and technical requirements, ensuring alignment between client goals and our solutions
• Architect tailored data solutions, encompassing cloud-native platforms, data integration, advanced analytics, and AI/ML models, to provide actionable business insights
• Develop competitive proposals, pricing models, and value propositions to successfully close opportunities and secure engagements
• Stay updated on emerging trends in Data & Analytics, Cloud, and AI, providing strategic advice to clients and supporting innovation within the practice
• Contribute to the development of reusable solution frameworks, accelerators, and methodologies to drive operational efficiency
• Act as a mentor and knowledge-sharer across the team, supporting skill-building and best practice dissemination

Requirements

• Extensive experience in presales, solution architecture, or consulting, with a focus on Data/AI technologies and related business use cases
• Strong technical knowledge in legacy Data Warehouse platforms (Oracle, DB2, Informatica, SSIS, etc.)
• Good experience in cloud data technologies (AWS, Azure, GCP)
• Experience in modern data platforms (Databricks, Snowflake)
• Familiarity with data science techniques and proficiency in analysis of client needs to align with technical solutions
• Excellent communication and storytelling skills—able to translate complex technical concepts into clear, client-friendly narratives
• Proven track record in engagement with senior stakeholders and delivery of impactful presentations or pitches
• Experience in creation of detailed proposals, RFP responses, and pricing/engagement models for data-related services or projects
• Understanding of strategic consulting principles and the ability to develop future-state recommendations and roadmaps for client success
• Strong organizational, leadership, and project scoping abilities, with a proven ability to manage complex tasks in a fast-paced environment
• Bachelor's or master's degree in data science, Computer Science, Business Analytics, or a related field (or equivalent professional experience)
• Excellent English communication skills, with the ability to clearly and effectively explain technical concepts to diverse audiences.

Our team is seeking a Data Solution Architect to further strengthen our capabilities.

Responsibilities

• Work closely with business in identifying solution requirements and key case-studies/scenarios to architect Data solution
• Participate in Data and Big Data initiatives on a company level
• Design Data analytics solutions by utilizing the Data technology stack with Big Data techniques
• Conduct solution architecture review/audit, calculate and present ROI
• Create and present solution architecture documents with deep technical details to customer and implementation teams
• Participate in specific “pre-sale” activities related to available experience and practice in order to prepare technical proposals on customer requests
• Lead implementation of the solutions from establishing project requirements and goals to solution "go-live"
• Maintain a strong understanding of technical solutions and architecture design trends and best practices, stay on cutting edge of Data technologies
• Constantly grow expertise by gathering and monitoring available EPAM project experience and ongoing projects with clients from different business domains to drive further EPAM business in Data field
• Create and follow personal education plan in the technology stack and solution architecture
• Share experience, knowledge and vision with EPAM, colleagues and customer teams. Participate in seminars, meet ups, mentoring, training programs. Prepare white papers and presentations

Requirements

• Strong ‘hands-on’ experience as a Data Architect with design/development background with Java, Scala, or Python
• Architecture experience and practice in Data Management, Data Storage, Data Visualization, Disaster Recovery, Integration, Operation and Security
• Experience with building traditional Cloud Data Warehouses, Data Lakes
• Knowledge of high load and IoT Data Platform architectures and infrastructures
• Wide experience in analysis, design, implementation, deployment as well as troubleshooting and rebuilding distributed Linux based platforms and Big Data solutions on premises and in Cloud
• Strong Cloud experience in at least one of the Cloud providers (AWS, Azure, GCP)
• Solid experience in continuous delivery tools and technologies
• Broad experience with Containers and Resource Management systems: Docker, Mesos, Kubernetes/OpenShift, Yarn
• Able to deliver Data Analytics projects and architecture guidelines
• Strong in research, comparison, and selection of tools / technologies / approaches to be used
• Practical experience in performance tuning and optimization, bottleneck problem analysis
• Strong communication skills, experienced in team coordination skills and solution implementation supervision
• Good in Agile development methodology, Scrum in particular
• Solid skills in business analysis, network/stack architecture, troubleshooting, support
• Fluent English

About the Role
We are seeking an AI & Data Science Consultant to drive the discovery, strategy, and end-to-end delivery of advanced AI initiatives for EPAM’s global clients. This role is a unique hybrid, blending strategic business consulting with deep practical engineering. You will collaborate directly with client executives and EPAM’s delivery teams to transform complex business challenges into scalable, production-ready AI, Machine Learning, and Agentic solutions.
 

Key Responsibilities

• Consult & Strategize: Lead client-facing discovery sessions and workshops to identify high-value AI opportunities, define MVP scopes, and map out strategic delivery roadmaps.
• Design & Architect: Shape scalable AI products incorporating Generative AI, RAG, multi-agent frameworks, semantic layers, and advanced analytics.
• Bridge the Collaboration: Serve as the central link connecting business stakeholders, data scientists, ML engineers, DevOps, and product teams.
• Drive Delivery & MLOps: Apply a strong engineering mindset to ensure solutions are secure, production-ready, and smoothly integrated into cloud infrastructures.
• Support Business Growth: Partner on pre-sales activities, solution estimation, and proposal development while contributing to EPAM’s internal AI and MLOps offerings.
   

Requirements

• Professional Experience: 3+ years of hands-on experience in Data Science, ML, or Applied AI, with a proven track record of bringing models from concept to production.
• Consulting & Communication: Strong active listening, presentation, and storytelling skills; ability to confidently translate complex AI concepts for C-level stakeholders.
• AI & Agentic Tech Stack: Experience with RAG, LLM applications, multi-agent orchestration, and tools like LangChain, LangGraph, CrewAI, LlamaIndex, or Vector DBs.
• Data & Architecture: Understanding of Semantic Layers, metadata, knowledge graphs, and data platforms (such as Databricks or Snowflake).
• Engineering & MLOps: Familiarity with the production model lifecycle, MLOps/LLMOps pipelines, and cloud platform integrations.
   

Nice to Have

• Experience mentoring cross-functional AI teams or driving enterprise-scale GenAI adoption.
• Practical knowledge of cloud infrastructure and DevOps tooling.
• Insights into AI governance and ethical AI frameworks.

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