Data Engineering Lead

About Qualysoft

· 25 years of experience in software engineering, established in Vienna, Austria · Active in Romania since 2007, with office in central Bucharest (Bd. Iancu de Hunedoara 54B) · Delivering End to End IT Consulting Services - From Team Augmentation and Dedicated Teams to Custom Software Development
· We deliver scalable enterprise systems, intelligent automation frameworks, and digital transformation platforms · Cross-industry experience by sustaining global players in BSFI (Banking, financial services and insurance), Telecom,Retail & E-commerce, Energy and Utilities, Automotive, Manufacturing, Logitics, High Tech · Global Presence: Switzerland, Germany, Austria, Sweden, Hungary, Slovakia, Serbia, Romania, and Indonesia · International team of 500+ software engineers · Strategic partnerships: Microsoft Cloud Certified Partner, Tricentis Solutions Partner in Test Automation and Test Management, Creatio Exclusive Partner, Doxee Implementation Partner · Powered by cutting-edge technologies: AI, Data & Analytics, Cloud, DevOps, IoT, and Test Automation. · Project beneficiaries ranging from large-scale enterprises to startups · Stable growth and revenue increase year over year, a resilient organisation in volatile IT market conditions · Quality-first mindset, culture of innovation, and long-term client partnerships · Global and local reach – trusted by key industry players in Europe and the US

Technical Leadership & Delivery • 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. Data Platform Engineering & Operations • 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. Solution Architecture & Consulting • 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. Presales & Business Development Support • 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 skills • 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. Professional and Leadership Skills • 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.