Jobs at Ness Digital Engineering

Develop backend-focused full-stack applications using Java, Node.js, Spring, REST APIs, messaging, and data processing. Contribute to frontend development with JavaScript or TypeScript and Vue.js or React, while supporting DevOps activities. Work with cloud platforms, containers, CI tools, databases, and scalable real-time telematics applications. Collaborate with a Kosice-based team to shape technical solutions and delivery for a long-term European client.

Develop and maintain complex full-stack web applications for telematics and mobility solutions. Responsibilities include front-end and back-end coding, application modification, collaboration with developers, testers, designers, DevOps engineers, and product teams, and participation in Agile/Scrum ceremonies. The role requires Java or Node.js backend development, TypeScript and JavaScript, Vue.js or comparable frontend frameworks, web technologies, REST APIs, Git, and cloud platform familiarity.

Build and support AI-enabled full-stack applications for finance technology. Develop UI, APIs, data access layers, and AI workflows such as chat, retrieval, document Q&A, and copilots. Maintain environments, logs, tests, documentation, and secure SDLC practices. Manage defects, enhancements, user support, demos, release materials, and delivery tracking while collaborating with the AI Lead, testers, and business users.

Administer and optimize large-scale Cloudera Hadoop environments, including cluster installation, configuration, monitoring, patching, node management, security, backups, disaster recovery, and performance tuning. Support production deployments, troubleshoot incidents, coordinate with support teams and vendors, and provide on-call coverage. The role requires hands-on expertise across Hadoop ecosystem technologies, Linux administration, automation, capacity planning, and high-availability operations.

Administer large and complex Cloudera Hadoop environments, including cluster installation, node management, configuration, monitoring, backups, patching, parcel updates, disaster recovery, and production deployments. Provide on-call support, coordinate with L1 and remote teams, escalate issues to Cloudera, optimize cluster performance, and implement automation and continual operational improvements.

Provides white-glove IT support for executives and end users, resolving application, device, access, and infrastructure issues. Responsibilities include ticket management, escalation, incident response, root cause analysis, hardware and software deployments, troubleshooting, documentation, knowledge-base maintenance, trend analysis, and leading migrations, rollouts, and other end-user technology projects. The role is onsite five days weekly with shifting hours and requires support across service desk, remote, phone, Teams, email, and walk-up channels.

Develop Python full-stack application modules across UI, application, integration, and database layers. Build Streamlit interfaces, PostgreSQL functionality, SQL queries, REST/API integrations, and multi-tenant components. Participate in testing, debugging, code reviews, and deployment while following established architecture and coding standards.

Lead full-stack Python development by translating architecture into detailed technical designs and application components. Build FastAPI applications deployed through Databricks Apps across UI, integration, and database layers. Develop core components, guide engineers, assign implementation work, review code, integrate PostgreSQL, and ensure multi-tenant isolation. Collaborate with architects to resolve technical issues and maintain alignment with enterprise architecture.

Designs end-to-end architectures for scalable, secure, multi-tenant SaaS applications using Python, Azure, and Databricks. Owns tenant isolation, deployment models, authentication, authorization, integrations, service boundaries, database and security layers, and technology selection. Produces architecture diagrams and modules while partnering with development leadership to translate architectural decisions into implementable components.

Supports quality assurance for Salesforce Service Cloud applications by executing functional, regression, and integration tests; maintaining automation scripts; validating Salesforce components and integrations; preparing test data; documenting defects in Jira or Copado DevOps; and collaborating with development, business analysis, and product teams in an Agile environment.

Builds and optimizes Azure Synapse environments replacing Alteryx workflows. Responsibilities include developing pipelines, SQL transformations, orchestration, CI/CD, security, performance tuning, ADLS optimization, monitoring, troubleshooting, and architectural guidance. The engineer collaborates with data modeling and conversion teams to deliver production-quality migrated workloads.

Leads enterprise data security and privacy assessments, identifies control gaps and exposure risks, and defines secure target-state architectures. Evaluates encryption, access governance, masking, tokenization, data minimization, and cloud or hybrid security controls. Develops remediation priorities, facilitates stakeholder workshops, supports risk assessments, and provides executive reporting while collaborating with architects, analysts, business stakeholders, and technology teams.

Develop datasets and interactive dashboards, analyze existing reports and data relationships, and support data warehousing across retail-focused product teams. Collaborate with project teams, business stakeholders, technical SMEs, and data insights teams. Apply SQL, Hadoop ecosystem tools, DataStage, database commands, and data extraction, cleansing, transformation, validation, and loading practices. Advocate development best practices and support data integration across applications and domains.

Provide technical customer support through email, chat, and phone; troubleshoot product and platform issues; guide customers toward solutions; collaborate with engineering and product teams on escalations; document resolutions; and maintain timely communication and customer satisfaction. The role requires operating-system, database, DevOps, infrastructure, troubleshooting, and basic scripting or Java knowledge in a SaaS or technology environment.

Provides senior-level technical support for hardware, software, networking, peripherals, and desktop applications. Resolves user tickets through on-site and remote assistance, guides users through troubleshooting, escalates unresolved issues, maintains ticket and maintenance records, advises on upgrades, verifies client system functionality, and creates technical reports and manuals.

Provides technical leadership and solution architecture for scalable, secure, cloud-native software platforms. Responsibilities include defining technology roadmaps, designing microservices and APIs, leading full-stack development with Python, SQL, AWS, and React, driving DevOps and CI/CD practices, overseeing delivery, mentoring engineers, and ensuring quality, security, observability, and stakeholder alignment.

Designs, builds, and maintains Snowflake-based ELT pipelines for data ingestion, integration, and transformation. Leads offshore data engineering teams, optimizes pipeline performance, implements data quality controls, troubleshoots failures, documents data flows, and ensures compliance with governance and security requirements. Collaborates with architects, project managers, analysts, and business stakeholders to deliver scalable data solutions.

Leads complex Salesforce engagements as the senior practitioner, owning solution architecture, requirements, impact assessments, delivery planning, client relationships, squad leadership, and commercial decisions. Designs changes for mature, highly customized multi-region orgs while tracing metadata, automation, integrations, and technical debt. Requires deep Sales Cloud and Revenue Lifecycle Management or CPQ expertise, strong stakeholder communication, agile delivery leadership, Salesforce certifications, and hands-on use of Salesforce CLI and VS Code.

Build and maintain cloud infrastructure across AWS and Azure using Terraform, Docker, Kubernetes, and CI/CD tooling. Develop automation, observability solutions, and operational infrastructure code while troubleshooting application environments. Apply machine learning fundamentals to data preprocessing, model training, evaluation, deployment, and production ML workflows. Collaborate with DevOps teams in complex corporate environments and communicate effectively in English.

Build and improve scalable data platforms, backend services, and data pipelines. Design data transformations, apply SQL-based modeling, troubleshoot complex systems, collaborate with stakeholders, contribute to architecture, and maintain code quality through testing, reviews, and documentation. The role requires strong software engineering fundamentals and analytical problem-solving, with opportunities to develop expertise in data engineering, analytics, cloud platforms, and data-intensive systems.