Databricks Developer - Banking

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

• Develop and maintain data ingestion, transformation, and publishing processes using Databricks and PySpark.
• Build and optimize ETL/ELT pipelines for large volumes of data.
• Implement Delta Lake structures and data models for operational and analytical consumption.
• Develop incremental loading, historization, and CDC (Change Data Capture) mechanisms.
• Integrate data from multiple sources, including Oracle, SQL Server, APIs, files, banking applications, etc.
• Participate in defining the Data Lakehouse architecture.
• Propose scalable and high-performance data models.
• Contribute to the development of development standards and platform architecture.
• Ensure data traceability and consistency throughout the entire processing flow.
• Implement automated Data Quality controls.
• Develop data reconciliation and validation processes.
• Configure monitoring, alerting, and process logging.
• Analyze and resolve production incidents.
• Manage data reloads, reruns, corrections, and recovery processes.
• Optimize PySpark and SQL processes for cost efficiency and performance.
• Identify and eliminate processing bottlenecks.
• Optimize Databricks resource consumption.
• Contribute to the automation of development and deployment processes.

Qualifications

• Minimum 5 years of experience in Data Warehouse development, Big Data, or enterprise data platforms.
• Minimum 2–3 years of hands-on experience with Databricks.
• Proven experience working on complex Data Warehouse, Data Mart, or Data Lake projects.
• Experience in developing end-to-end data pipelines.
• Strong knowledge of Data Lakehouse architecture.
• Experience implementing historization, CDC, data reconciliation, and Data Quality processes.
• Ability to take full ownership of technical deliveries and provide technical leadership to the team.
• Technical skills: Azure Databricks / PySpark, Advanced SQL, Delta Lake, Git & Jira, Data Modelling, ETL / ELT,

Data Quality Frameworks, Pipeline Orchestration.