Data Engineer

ConnectPoint specializes in delivering IoT, IT/OT solutions, and proprietary IT products for industry. They provide technologies supporting production process monitoring, energy optimization, system integration, software development, data processing and reporting, GIS, BI, and competencies in machine learning and big data. Their clients include large international corporations as well as local energy, water, and heat suppliers.

• Minimum 3 years of experience as a Data Engineer
• Very good knowledge of Python and SQL
• Experience in designing and building data pipelines, especially streaming and event data processing
• Knowledge of event-driven architecture and tools for real-time data processing (e.g., Apache Kafka, Kafka Connect, Apache Flink, Spark Structured Streaming, Apache Pulsar, Azure Event Hubs, Google Pub/Sub)
• Knowledge of relational databases and technologies for modern data platforms
• Familiarity with Git and CI/CD processes
• Experience with selected technologies in these areas:
  • Open Source Data: Apache Kafka, Spark, Flink, Trino, Hive
  • Public clouds: Azure, AWS, Google Cloud
  • Orchestration and integration: Airflow, NiFi
  • Storage: S3-compatible Object Storage, Azure Storage, GCS
  • Data formats: Iceberg, Delta Lake
  • Databases: PostgreSQL, TimescaleDB, SQL Server
• Ability to monitor data quality and diagnose performance issues
• Comfortable cooperating with clients and understanding business needs
• Communication skills and English language proficiency enabling daily work

• Design, implement, and develop platforms and processes for real-time and batch data processing
• Build and develop architecture based on event streaming and integrate systems exchanging real-time data
• Create and optimize data pipelines and data models for analytical and operational systems
• Design reliable, scalable solutions cooperating with the DevOps team
• Support clients from Energy, Utilities, and Manufacturing in building modern data platforms