Data Solution Architect

EPAM Systems; United States; Remote; USD 140.000 - 190.000; Vollzeit

Zusammenfassung

EPAM Systems is seeking a Data Solution Architect for data-driven projects in the United States. You will design and drive scalable data platforms, leveraging cutting-edge technologies and ML algorithms to empower digital transformation and data democratization.

The role requires hands-on involvement across architecture, engineering, and governance, coordinating with stakeholders to align data strategy with business goals. Strong English and cross-domain experience are essential.

Qualifikationen

• Experience in requirements engineering and solution architecture.
• Knowledge of architecture design patterns and tech landscape in multiple domains (Data Platforms, IoT, ML, Backend, Mobile, etc.).
• Profound knowledge of at least one technology domain internals.
• Solid understanding of data warehousing, BI, data management, integration, security and operations.

Aufgaben

• Address business goals with best practices in data, solution, enterprise, and software architectures.
• Conduct architectural activities: analyze problems, identify requirements, design solutions, artifacts.
• Perform hands-on software engineering: write code and data models across stacks; read data models and code.

Kenntnisse

Requirements engineering

Solution architecture

Systems development

Data platforms

Cloud & on-prem

Data governance

Security & compliance

Communication

English fluency

Jobbeschreibung

We are seeking a Data Solution Architect for data-driven projects. Together, we design and drive lots of solutions that generate value from data, taking advantage of scalable platforms, cutting-edge technologies, and machine learning algorithms. Data Solution Architect is an expert who empowers an organization's digital transformation through enterprise data enablement and democratization.

Responsibilities

• Address organization business goals and strategy with best practices in data-, solution-, enterprise- and business- architectures, as well as in software engineering
• Conduct various architectural activities, which include analysis of business problems and technology landscape, identification of significant requirements, design of solutions and creation of corresponding artifacts
• Perform hands-on software engineering activities, i.e., write code and create data models in primary technology stacks, read/understand code and data models for non-primary technology stacks, apply software design patterns and practices
• Build data management environments (data platforms), where data and AI products can be produced and hosted, both on premise and in the cloud, with consideration of security, compliance and regulatory limitations, including automation and operational components, monitors, platform orchestration, batch and streaming data ingestion, data access layer, metadata management and semantic layer, self-service and exploratory environment, CI/CD and infrastructure automation, capacity and cost management components; as well as interfaces for reports of data flow and data quality metrics, operational statuses, and catalog operations
• Guide implementation team efforts in integration and harmonization of data from different sources, construction of analytical data products (including real-time streaming analytical data products) on its basis within the data platform, as well as management of data products life cycle end-to-end, with assurance of their data quality, security and privacy, and doing it efficiently at scale
• Drive data technology consulting services, help clients to shape a vision of the solution and make decisions under uncertainty

Requirements

• Experience in requirements engineering, solution architecture, systems development, deployment and maintenance
• Knowledge of architecture, design patterns and technological landscape in at least 3 technology domains (Data Platforms, IoT, ML, Backend, Mobile, etc.)
• Profound knowledge of the technology's internals for at least 1 technology domain
• Solid understanding of the core concepts in data and analytics platform architectures, data warehousing, business intelligence, data management, integration, security and operations areas
• Wide experience in design, implementation, deployment, troubleshooting and re-platforming of distributed systems both on premises and in the Cloud
• Structured and systematic knowledge of the entire of architecture design process (requirements, quality attributes, technology selection, estimation, proposal verification, documentation, etc.)
• Experience in all phases of the software development life cycle with different development methodologies and best practices
• Highly organized and detail-oriented
• Good communication skills
• Fluent English