Data Engineering Lead

About the role

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.