Data Engineer- Romania

We are looking for an experienced Data Engineer to join our data team and play a key role in designing, building, and maintaining scalable data solutions. The successful candidate will work on data ingestion, transformation, processing, and integration, ensuring that data is reliable, accessible, secure, and optimized for analytics and business use cases. You will collaborate closely with Data Scientists, Data Analysts, Software Engineers, Cloud Engineers, and business stakeholders. Responsibilities Design, develop, and maintain scalable data pipelines and ETL/ELT processes. Build reliable data ingestion solutions from multiple sources, including databases, APIs, files, and cloud storage. Develop and optimize data transformation workflows for structured and unstructured data. Design and maintain data models, data warehouses, and data lakes. Ensure data quality, consistency, accuracy, and availability across different data platforms. Develop efficient and reusable SQL queries and data processing solutions. Implement data validation, monitoring, and error-handling mechanisms. Optimize data pipelines and workloads for performance, scalability, and cost efficiency. Integrate data from multiple systems and ensure seamless data flow between platforms. Work with cloud-based data services and contribute to the development of cloud-native data architectures. Implement automated testing and data quality checks. Monitor production data pipelines, investigate failures, and perform root-cause analysis. Collaborate with DevOps and engineering teams to implement CI/CD for data solutions. Participate in architecture and technical design discussions. Maintain technical documentation for data pipelines, processes, and architecture. Follow best practices related to security, governance, access control, and data protection. Required Skills & Experience 3+ years of professional experience in Data Engineering or a similar role. Strong proficiency in SQL and experience working with large datasets. Hands-on experience with Python for data processing and automation. Solid experience with ETL/ELT pipelines and data integration. Experience with relational databases such as PostgreSQL, SQL Server, Oracle, or MySQL. Good understanding of data warehousing and data modeling concepts. Experience with at least one cloud platform: AWS, Azure, or GCP. Experience working with cloud storage and data processing services. Familiarity with distributed data processing technologies such as Apache Spark or PySpark. Experience with orchestration tools such as Apache Airflow, Azure Data Factory, or similar. Good understanding of data lake and data warehouse architectures. Experience with Git and modern software development practices. Familiarity with CI/CD processes and tools. Strong analytical and problem-solving skills. Ability to work effectively in a collaborative Agile environment. Nice to Have Experience with modern data platforms such as Snowflake, Databricks, BigQuery, or Redshift. Knowledge of Apache Kafka or other event-streaming technologies. Experience with dbt or similar data transformation frameworks. Experience with Kubernetes and Docker. Knowledge of Infrastructure as Code, particularly Terraform. Experience implementing data quality and observability solutions. Knowledge of data governance, metadata management, and data cataloguing. Experience working with real-time or near-real-time data processing. Familiarity with BI and analytics platforms such as Power BI or Tableau. Experience working with machine learning or AI data pipelines is a plus. Soft Skills Strong communication and collaboration skills. Ability to translate business requirements into technical data solutions. Proactive approach to identifying and solving technical challenges. Strong attention to detail and commitment to data quality. Ability to work independently and take ownership of assigned tasks. Willingness to learn new technologies and continuously improve technical skills.