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Design and develop scalable, reliable data platforms and pipelines for analytics and operations
Implement data processing workflows using distributed frameworks (Apache Spark/pySpark, Databricks)
Evolve the organization’s cloud data platform leveraging Azure technologies (Data Factory, Synapse, Event Hub, Azure Data Lake Storage)
Model data to support analytics, reporting, and downstream consumption
Integrate and process data from multiple sources ensuring quality and consistency
Monitor and optimize pipeline performance, ensuring reliability and scalability
Collaborate with analysts, scientists, and engineers to translate requirements into solutions
Improve data engineering standards, testing, and operational reliability
Evaluate and introduce new tools and technologies in the data engineering ecosystem
4+ years of hands-on experience in data engineering or building data processing platforms
Strong SQL skills and solid Python experience for pipeline development
Experience with distributed processing frameworks (Apache Spark/pySpark, Databricks preferred)
Practical experience designing and implementing pipelines in cloud environments (Azure preferred)
Experience with production-scale analytical systems and data modeling
Understanding of ETL/ELT design, dimensional modeling, and data warehousing principles
Experience with modern data lake architectures and formats (Parquet, JSON)
Familiarity with workflow orchestration tools (Airflow)
Experience with database development and optimization
Ability to design scalable solutions with minimal supervision
Strong collaboration and communication skills
Professional proficiency in English
Are you passionate about building scalable, high-performance data solutions? We are looking for a Data Engineer to join our team and help design and develop robust data platforms that power analytics, reporting, and data-driven decision-making.
Why join us? You will work on challenging projects, collaborate with talented experts, and have access to professional growth opportunities, a supportive environment, and competitive benefits.