Lead Data Engineer (Azure)
# Lead Data Engineer (Azure) **Softserve** · Remote · `Remote` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Get on Board (LATAM)* --- ### About the Role - 5+ years of experience in Data Engineering, including hands-on development of ETL pipelines and data integration solutions - +2 years of experience as Data Engineer Lead - Advanced proficiency in SQL and Python for data processing, transformation, and optimization - Strong experience with Spark and PySpark for distributed data processing - Hands-on experience with Azure data technologies and cloud-based data platforms - Advanced proficiency with Azure Synapse, Azure Data Factory and/or Apache Airflow for workflow orchestration and scheduling - Strong understanding of Data Architecture, Data Modeling, Data Quality, Data Integration, and SQL and ETL performance optimization - Proven ability to provide technical guidance to engineering teams and serve as a technical reference throughout project delivery - Strong working proficiency in English for daily communication with international clients and teams - Client-facing, communication, analytical, and problem-solving skills - Design and develop scalable ETL and data integration pipelines across Azure data environments - Own technical implementation and solution quality, ensuring reliable, scalable, and maintainable data processing - Collaborate with clients, Solution Architects, and engineering teams to translate business requirements into effective data solutions - Build and optimize data processing workflows using SQL, Python, Spark, PySpark, Azure Data Factory, and Apache Airflow - Develop data models and schemas aligned with business requirements, architecture standards, and downstream consumption needs - Implement data quality and validation controls to maintain data integrity and consistency across platforms - Optimize SQL queries, ETL processes, and data workflows to improve performance and reliability - Guide the Data Engineering team on technical decisions, engineering practices, troubleshooting, and successful solution delivery - Exposure to Microsoft Fabric, Hadoop, Hive, Kafka, Power BI, or Tableau as a plus - Experience with healthcare or pharmaceutical data environments as an advantage
Наблюдалась 2026-10-16, впервые 2026-10-15, источник — Get on Board (LATAM).