Data Analytics Software Architect

Overview

As a Data Analytics Software Architect, you will lead hands-on product delivery while owning the architectural direction for a scalable, secure data analytics ecosystem. You’ll align with Enterprise Architecture to translate strategy into practical solutions, building AI-enabled capabilities and agentic AI solutions that drive business value. You’ll mentor engineers, guide delivery across multiple products, and continuously improve engineering practices in a hybrid, collaborative environment.

Pay / Benefits

• professional development opportunities
• inclusive culture
• flexible benefits package up to 20% of annual salary
• 30+ days off
• performance bonus scheme
• core benefits: pension, life and medical insurance

Responsibilities

• Lead by example as a hands-on product builder to deliver the organization’s goals
• Drive tactical plans to implement Product Ecosystem strategies defined by Enterprise Architects
• Own and shape the underlying architecture for the Product Ecosystem ensuring scalability, security, and maintainability
• Maintain high engineering quality by establishing practices, guardrails, and AI-assisted delivery patterns
• Interface between Software Engineering, Enterprise Architecture, and management for alignment and clarity
• Oversee technical delivery across teams and support Lead/Senior Engineers’ development
• Design detailed solution architectures with Enterprise Architects and engineers (backend/frontend as needed)
• Facilitate broad collaboration and design decisions across teams
• Review designs and provide constructive feedback with architecture group
• Guide development techniques and methodologies (Agile at Scale, Lean, CI/CD, TDD, IaC)
• Drive continuous improvement to enhance delivery effectiveness
• Track progress toward engineering goals and report status to engineers, EA, and management
• Research and evaluate new technologies and approaches benefiting the organization
• Contribute to thought leadership and strategy across Software Engineering
• Build cloud-based data and analytics solutions including Agentic AI solutions with governance

Key requirements

• Excellent written and spoken Romanian and English
• Proven experience as Lead or Senior Engineer across multiple products, ready for Architect level
• Strong ability to communicate with technical and non-technical stakeholders in cross-functional settings
• Proven track record delivering software across diverse languages, technologies, and platforms
• Strong leadership and people skills with coaching/mentoring mindset
• Experience with cloud-native architectures and modern engineering practices (Agile at Scale, Lean, CD, CI, TDD, IaC)
• Knowledge of CI/CD and DevOps practices, including Quality Gates
• Security-driven design practices and remediation of SAST/DAST findings
• SDLC tools: Confluence, Jira, Azure DevOps (ADO), GitHub (or equivalents)
• Experience designing and deploying apps on AWS and Microsoft Azure
• Data and analytics platform experience (warehousing, data lakes/lakehouses, ETL/ELT, streaming, BI, integration platforms)
• ML/AI solution architecture, model lifecycle, governance
• Agentic AI solutions development and application of AI to business use cases
• Broad programming with JavaScript/TypeScript/C#, with Angular, .NET, Less/Sass, gRPC
• Testing discipline (unit and integration testing)
• Containers and platforms (Docker, Kubernetes)
• ORMs and databases (MSSQL, NoSQL MongoDB)
• Middleware (RabbitMQ, MassTransit) powered skills

• Strong communication with stakeholders
• Collaborative and leadership mindset
• Coaching and mentoring for career development
• Cloud-native architectures (AWS, Azure)
• Data and analytics platforms (data warehouses/lakes, ETL/ELT, streaming, BI)
• Agentic AI and AI governance

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