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Data Engineer

Sigmasoftware2

Sigmasoftware2 is the employer — EngRadar is a job radar, not a recruiter. We track this posting from their own careers page and send you straight there; we never handle applications or CVs.

Remote Kyiv, Kyiv city, Ukraine Full-time Posted 2d ago

Responsibilities

  • Design and develop scalable and reliable data platforms and/or data pipelines for analytical and operational use cases
  • Design and implement data processing workflows using distributed processing frameworks such as Apache Spark/pySpark (Databricks)
  • Contribute to the evolution of the organization’s cloud data platform using Azure technologies (e.g., Azure Data Factory, Synapse, Microsoft Fabrik, Databricks, Event Hub, Azure Data Lake Storage)
  • Strong background in data modelling to support analytics, reporting, and downstream data consumption
  • Integrate and process data from multiple internal and external sources while ensuring data consistency, quality, and reliability
  • Take ownership of data pipeline reliability, monitoring, and performance, ensuring scalable and maintainable data processing workflows
  • Collaborate with data analysts, data scientists, and engineering teams to translate business and analytical requirements into robust data solutions
  • Drive improvements in data engineering practices, including pipeline design standards, testing approaches, and operational reliability
  • Participate in evaluating and introducing new tools and technologies within the data engineering ecosystem

Required Qualifications

  • Strong hands-on experience (4+ years) in data engineering or building data processing platforms
  • Strong SQL skills and solid experience with Python for building and maintaining data pipelines
  • Experience working with distributed data processing frameworks such as Apache Spark/pySpark (Databricks experience is a strong advantage)
  • Practical experience designing and implementing data pipelines in cloud environments, preferably within the Azure ecosystem
  • Experience designing data pipelines and data models for production-scale analytical systems
  • Strong understanding of data engineering concepts including ETL/ELT design, dimensional modeling, and data warehousing principles
  • Experience working with modern data lake architectures and data formats such as Parquet and JSON
  • Experience with workflow orchestration tools (e.g., Airflow)
  • Experience with database development and performance optimization
  • Ability to design scalable and maintainable data solutions with minimal supervision
  • Strong collaboration and communication skills
  • Professional working proficiency in English

Nice to Have

  • Experience with modern cloud data warehouses such as Snowflake, BigQuery, or Redshift
  • Experience with streaming data technologies (e.g., Event Hub, Kafka, Spark Streaming)
  • Experience with Delta Lake or other lakehouse technologies
  • Familiarity with CI/CD practices and Git-based development workflows
  • Experience working in agile development environments

 

 

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