Data Engineer

This is a fully remote position, open to applicants in Ukraine.

📋 Description

• Create and develop scalable and dependable data platforms and/or data pipelines for both analytical and operational purposes.

• Design and execute data processing workflows utilizing distributed processing frameworks like Apache Spark/pySpark (Databricks).

• Contribute to the advancement of the organization’s cloud data platform with Azure technologies, including Azure Data Factory, Synapse, Microsoft Fabric, Databricks, Event Hub, and Azure Data Lake Storage.

• Integrate and manage data from various internal and external sources while maintaining data consistency, quality, and reliability.

• Assume responsibility for data pipeline reliability, monitoring, and performance.

• Collaborate with data analysts, data scientists, and engineering teams to convert business and analytical requirements into effective data solutions.

• Promote enhancements in data engineering practices, including pipeline design standards, testing methodologies, and operational reliability.

• Engage in assessing and introducing new tools and technologies within the data engineering ecosystem.

⛳️ Requirements

• Extensive hands-on experience (4+ years) in data engineering or developing data processing platforms.

• Proficient SQL skills and solid experience with Python for constructing and maintaining data pipelines.

• Experience with distributed data processing frameworks such as Apache Spark/pySpark (Databricks experience is highly advantageous).

• Practical experience in designing and implementing data pipelines in cloud environments, ideally within the Azure ecosystem.

• Experience in designing data pipelines and data models for large-scale analytical systems.

• Strong comprehension of data engineering concepts, including ETL/ELT design, dimensional modeling, and data warehousing principles.

• Experience with contemporary data lake architectures and data formats like Parquet and JSON.

• Familiarity with workflow orchestration tools (e.g., Airflow).

• Experience in database development and performance tuning.

• Ability to design scalable and maintainable data solutions with minimal oversight.

• Excellent collaboration and communication skills.

• Professional working proficiency in English.

• Experience with modern cloud data warehouses such as Snowflake, BigQuery, or Redshift.

• Familiarity with streaming data technologies (e.g., Event Hub, Kafka, Spark Streaming).

• Experience with Delta Lake or other lakehouse technologies.

• Understanding of CI/CD practices and Git-based development workflows.

• Experience working in agile development settings.

🏝️ Benefits

• Employees have the flexibility to work remotely.