Salary
≈ $39k – $89k per year (Estimated)
Location
Hybrid (Bucharest, Romania)
Seniority
Staff · 7+ years exp
Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Oct 21, 2026. Qualysoft scores B on the Alion truth index.
Overview
Company
Impact
Profile match
Qualysoft is an international IT services, enterprise software engineering, and digital transformation consultancy headquartered in Vienna, Austria. Founded in 1999 by Peter Oros and Martin Schwarz, the privately held firm operates across Central and Eastern Europe with office hubs in Austria, Germany, Switzerland, Sweden, Hungary, Slovakia, Serbia, Romania, and Indonesia.
Responsibilities
- Lead Data Engineering projects, ensuring high-quality technical delivery and alignment with customer requirements.
- Provide technical guidance, mentoring, and support to Data Engineering teams.
- Design and implement scalable data architectures, data pipelines, and integration solutions.
- Drive technical decisions and establish engineering standards, best practices, and quality assurance processes.
- Ensure the reliability, performance, security, and maintainability of data platforms.
- Identify and resolve complex technical challenges throughout the project lifecycle.
- Collaborate with project managers and cross-functional teams to ensure successful project execution.
- Design, develop, and optimize modern cloud-based data platforms, primarily using Databricks.
- Build and maintain robust ETL/ELT pipelines and data processing workflows.
- Implement data orchestration, automation, monitoring, and performance optimization solutions.
- Support the operation and continuous improvement of enterprise data environments.
- Establish effective DataOps practices, including CI/CD, automated testing, incident resolution, and operational monitoring.
- Ensure compliance with data governance, security, and data quality requirements.
- Work directly with customers to understand business objectives, technical requirements, and operational challenges.
- Translate business requirements into scalable, cost-effective, and sustainable technical solutions.
- Lead technical workshops, architecture discussions, and solution design sessions.
- Provide expert guidance on data platform architecture, modernization, integration, and optimization.
- Prepare technical documentation, architectural designs, and implementation recommendations.
- Act as a trusted technical advisor to customer stakeholders.
- Contribute to technical proposals, solution designs, and effort estimations for new opportunities.
- Support RFP and tender responses by defining technical approaches, architectures, and delivery concepts.
- Participate in customer presentations, technical demonstrations, and discovery workshops.
- Collaborate with Sales, Account Management, and Solution teams to identify and develop new opportunities.
- Contribute to the development and standardization of Data Engineering and Data Operations service offerings.
Technical Leadership & Delivery
Data Platform Engineering & Operations
Solution Architecture & Consulting
Presales & Business Development Support
Qualifications
- Minimum 7 years of professional experience in Data Engineering, Data Architecture, or related disciplines.
- Strong hands-on experience with Databricks, Apache Spark, and Delta Lake.
- Advanced proficiency in Python and SQL.
- Solid understanding of modern data architectures, including Data Lake, Data Warehouse, and Lakehouse concepts.
- Proven experience designing and implementing ETL/ELT pipelines and complex data integration solutions.
- Strong experience with cloud-based data platforms (Azure, AWS, or Google Cloud), preferably in combination with Databricks.
- Knowledge of data orchestration, workflow automation, and CI/CD practices.
- Experience using AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, Claude) to improve coding productivity, troubleshooting, testing, and documentation.
- Experience with performance optimization, data quality, monitoring, and troubleshooting.
- Understanding of data governance, access management, and security principles.
- Familiarity with production-grade data platform operations and DataOps methodologies.
- Proven experience in a technical leadership role, such as Lead Data Engineer, Technical Lead, or Data Architect.
- Experience in IT consulting, systems integration, or professional technology services.
- Ability to identify and drive opportunities for applying AI-powered tools and automation to improve Data Engineering efficiency, delivery quality, and team productivity.
- Strong analytical and problem-solving capabilities.
- Ability to translate business requirements into technical architectures and implementation plans.
- Experience managing technical stakeholders and working directly with enterprise customers.
- Strong communication, presentation, and consulting skills.
- Ability to work independently while coordinating cross-functional and international teams.
- Experience preparing technical proposals, estimates, and solution documentation.
- Strong ownership mindset, proactive attitude, and commitment to delivery excellence.
- Fluent English, both written and spoken.
Technical skills
Professional and Leadership Skills
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