Lead Data Engineer- Romania

We are looking for an experienced Lead Data Engineer to lead the design, development, and implementation of scalable and reliable data solutions. The role combines hands-on technical expertise with technical leadership, requiring close collaboration with data engineers, data scientists, architects, and business stakeholders.
The ideal candidate will have strong experience in data engineering, cloud platforms, data architecture, and modern data technologies, with a proven ability to lead technical initiatives and mentor engineering teams.
Key Responsibilities
Lead the design and development of scalable, secure, and high-performance data platforms and pipelines.
Define and implement data engineering best practices, standards, and architectural patterns.
Lead the development of ETL/ELT pipelines and data integration solutions.
Design and optimize data models, data warehouses, data lakes, and lakehouse architectures.
Ensure data pipelines are reliable, maintainable, scalable, and optimized for performance and cost.
Work closely with Data Scientists, BI Developers, Software Engineers, Solution Architects, and business stakeholders.
Provide technical leadership and mentorship to Data Engineers and support their professional development.
Review technical designs and code, ensuring high standards of quality, scalability, and maintainability.
Identify opportunities to improve data processing, automation, performance, and operational efficiency.
Implement data quality, governance, security, and monitoring practices.
Troubleshoot complex data and production issues and drive root cause analysis.
Contribute to cloud and data platform architecture decisions.
Stay up to date with emerging technologies and recommend appropriate solutions for the organization's data strategy.
Must-Have Skills
6+ years of experience in Data Engineering or a related field.
Proven experience in a technical leadership or Lead Data Engineer role.
Strong proficiency in Python and/or SQL.
Extensive experience designing and developing ETL/ELT data pipelines.
Strong knowledge of data warehousing, data lakes, and data modeling.
Hands-on experience with distributed data processing technologies such as Apache Spark / PySpark.
Strong experience with at least one major cloud platform: AWS, Azure, or GCP.
Experience with modern data platforms such as Databricks, Snowflake, BigQuery, Synapse, or equivalent.
Strong understanding of relational and NoSQL databases.
Experience with workflow orchestration tools such as Apache Airflow, Azure Data Factory, or similar.
Strong knowledge of data integration and API-based data ingestion.
Experience with Git and CI/CD practices.
Strong understanding of data quality, security, governance, and observability.
Excellent problem-solving and analytical skills.
Strong communication and stakeholder management skills.
Fluent English.
Nice-to-Have Skills
Experience with Data Lakehouse architectures.
Knowledge of Delta Lake and modern lakehouse technologies.
Experience with Kafka or other event-streaming technologies.
Experience with Terraform or other Infrastructure as Code tools.
Knowledge of Kubernetes and containerized data workloads.
Experience implementing DataOps or DevOps practices for data platforms.
Experience with ML/AI data pipelines and machine learning platforms.
Knowledge of data governance and cataloging tools such as Microsoft Purview, Collibra, or similar.
Experience with real-time and streaming data processing.
Familiarity with FinOps and cloud cost optimization.
Experience working in Agile/Scrum environments.

Work arrangement
Yes