Medior Data Engineer Java Full Stack_Data Platform

• Full Stack Development: Design, develop, and deploy full stack data solutions, including both front-end (user interface) and back-end (data processing and storage) components. Test solutions, monitor systems and develop integrations with other applications.
• API Development and Integration: Create and maintain APIs to facilitate seamless data exchange between different systems and applications.
• Data Pipeline Construction: Design and build robust data pipelines that ensure smooth data flow from multiple sources to data warehouses or lakes. These pipelines enable organizations to make data-driven decisions by providing a unified and reliable data source. Perform data analysis, implement data models, and optimize queries for performance.
• Continuous Integration/Continuous Deployment (CI/CD): Implement and manage CI/CD pipelines to automate testing, deployment, and monitoring of data applications.
• Incident Management: Lead the troubleshooting and resolution of complex incidents related to data pipelines, applications, and integrations, ensuring minimal downtime and disruption.
• Analyze data, design and build physical models at the various stages of the data pipeline: ingestion of data sources, mapping in data marts for consumption.
• Build processes supporting data transformation, data structures, metadata and data blueprints.
• Work closely with senior data engineers to understand complex architectural designs and implement solutions as part of larger initiatives.
• Implement data quality checks and support ongoing monitoring to proactively resolve issues.
• Collaborate with the infrastructure teams to optimize data storage, processing, and performance.
• Support the execution of programs and projects in the role of Developer and Technical Analyst.
• Provide support in mentoring junior engineers and contribute to knowledge-sharing sessions within the team.
• Data Quality Assurance: implement data cleaning and validation processes to enhance data accuracy and consistency, addressing one of the key challenges data analysts face.
• Scalability: design systems that can handle large volumes of data, ensuring that as an organization grows, its data infrastructure can scale accordingly.
• ETL (Extract, Transform, Load) Processes: perform design and implementation of scalable and reliable ETL processes to transform raw data into structured formats.
• Data Security: Maintain data security best practices in collaboration with security

• 3 years of experience in data engineering, with a focus on building and maintaining data pipelines.
• Experience with big data technologies such as Hadoop, Spark, or Kafka.
• Exposure to cloud-based data platforms like AWS, Azure, or Google Cloud.

• Proficiency in front-end technologies (HTML, CSS, JavaScript) and frameworks like React, Angular,
• Strong knowledge of back-end technologies such as , Python, Java, with experience in building RESTful APIs and microservices.
• Strong knowledge on Spring / Spring Boot framework.
• Expertise in SQL and experience with relational databases, including complex query optimization and performance tuning, including ORM like Hibernate.
• Experience with Continuous Integration/Continuous Deployment (CI/CD) practices and tools
• automate and streamline data pipeline deployments like Jenkins.
• Familiarity with Data Orchestration tools (e.g. JCL Mainframe Job Scheduler, Apache Airflow, Databricks Workflows, Azure Data Factory, Google Cloud Composer, Crontab, etc.)
• Familiarity with the Linux operating system commands and scripting capabilities.
• Strong understanding of data modeling principles, data architecture best practices, and data governance frameworks.
• Knowledge of containerization (Docker) and orchestration tools (Kubernetes) is a plus.
• Familiarity with modern development practices such as DevOps and Agile methodologies.
• Familiarity with data warehousing solutions like Teradata, Snowflake, Redshift, or BigQuery.
• Experience with ETL tools (e.g., Talend, Apache NiFi, Informatica, Data Stage).
• Wiliness to learn and experiment with new technologies (e.g. Dremio, Apache Kafka, Apache Airflow, etc.).
• Understanding of data modeling principles and best practices in data architecture.

• Problem-solving mindset, good prioritization skills and the ability to work in a fast-paced environment.
• Good communication skills, with the ability to work well in a team environment.
• Effective communication skills for interacting with both technical and non-technical stakeholders.
• Fluent written and spoken English.

• #MakeInnovationHappen: Chance to make an impact in terms of transformation
• #UnlockYourPotential: Join a young and stimulating environment
• #ComeAsYouAre: Working within a global team
• #UnlockYourPotential: Play a role of autonomy with high visibility and exposure
• #BalanceLifeAndCareer: Flexible working hours;
• #BalanceLifeAndCareer: The possibility of working hybrid;
• A professional but still friendly work environment;
• #EnjoyTheBest: Access to our Benefits platform with a dedicated budget that you will be able to use, in order to choose the most suitable benefits for you;
• Healthcare services from one of the agreed providers;
• Holidays accorded based on your working experience (21 up to 25 days);
• Career in a leading international banking group, build on the diversity of its strong local roots;
• Dynamic and multinational environment, full of growing opportunities.

Unicredit S.p.A. - Romania Branch