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

Responsibilities

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.

Qualifications

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.