Lead Data Engineer-Romania

We are looking for an experienced Lead Data Engineer to lead the design, development, and delivery of scalable data platforms and pipelines. The role combines strong hands-on technical expertise with technical leadership, architecture, and collaboration across engineering, analytics, and business teams.
The ideal candidate has extensive experience in data engineering, cloud technologies, distributed data processing, and modern data architectures, together with strong leadership and communication skills.
Responsibilities
Lead the design and implementation of scalable, reliable, and high-performance data platforms and pipelines.
Define data engineering standards, best practices, and architectural principles.
Provide technical leadership and guidance to Data Engineers and other technical team members.
Design and optimize ETL/ELT pipelines for processing large volumes of structured and unstructured data.
Develop robust data ingestion, transformation, and integration solutions.
Work closely with Data Scientists, Data Analysts, Software Engineers, and business stakeholders to understand data requirements.
Ensure data pipelines are reliable, scalable, secure, and maintainable.
Drive performance optimization and troubleshoot complex data engineering issues.
Establish and maintain data quality, monitoring, governance, and observability practices.
Contribute to the definition and evolution of the organization's data architecture.
Lead technical discussions, architecture reviews, and code reviews.
Identify opportunities to improve data platforms, processes, and engineering practices.
Support CI/CD implementation and automation for data engineering workflows.
Ensure compliance with security, privacy, and data governance standards.
Mentor team members and contribute to their technical development.
Collaborate with cross-functional and international teams in an Agile environment.
Requirements
7+ years of professional experience in Data Engineering or a related field.
Strong experience with Python and/or SQL.
Extensive experience designing and developing ETL/ELT pipelines.
Strong knowledge of data warehousing, data modeling, and database technologies.
Experience with distributed data processing technologies such as Apache Spark / PySpark.
Hands-on experience with modern cloud data platforms, preferably Azure, AWS, or GCP.
Experience with technologies such as Databricks, Snowflake, BigQuery, Redshift, or Synapse Analytics.
Strong understanding of data architecture, data integration, and distributed systems.
Experience with relational and NoSQL databases.
Strong knowledge of Git, CI/CD, and Infrastructure as Code concepts.
Experience with data orchestration tools such as Apache Airflow, Azure Data Factory, or similar.
Strong understanding of data quality, governance, security, and monitoring.
Proven experience providing technical leadership and mentoring engineers.
Excellent problem-solving and analytical skills.
Strong communication and stakeholder management skills.
Ability to work effectively in a fast-paced, international environment.
Nice to Have
Experience with Kafka or other event-streaming technologies.
Experience with Kubernetes and Docker.
Knowledge of Terraform or other Infrastructure as Code tools.
Experience with Data Mesh, Lakehouse, or modern data architecture patterns.
Knowledge of MLOps, AI/ML data pipelines, or Generative AI.
Experience with data governance and cataloging tools.
Experience working with real-time/streaming data processing.
Previous experience as a Tech Lead, Lead Data Engineer, or Data Architect.
Key Skills
Python | SQL | PySpark | Apache Spark | ETL/ELT | Data Warehousing | Data Modeling | Cloud | Databricks | Snowflake | BigQuery | Airflow | Kafka | CI/CD | Data Architecture | Data Governance | Technical Leadership

Work arrangement
Yes