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 and local energy, water, and heat suppliers.

• Minimum 3 years of experience as a Data Engineer
• Very good knowledge of Python and SQL
• Familiarity with relational databases, data warehouse solutions, data lake and data lakehouse platforms
• Experience with version control systems like Git and basics of CI/CD
• Experience with at least one technology from the following areas:
  • Data platforms: Databricks, Snowflake, MS Fabric, Synapse, BigQuery, or open-source (Hive, Trino, Apache Spark)
  • Public clouds: Azure, Google Cloud, AWS, or private clouds
  • ETL/ELT tools: Apache Airflow, NiFi, Azure Data Factory, Google Dataflow, Dataproc
  • Storage: S3-compatible Object Storage, Azure Storage Account, GCS
  • Data formats: Delta Lake, Iceberg
  • Databases: PostgreSQL, SQL Server, Oracle
• Ability to implement data quality mechanisms for data processing verification
• Ability to diagnose performance issues and optimize data processing
• Ability to collaborate with clients and understand their business needs
• Communication skills and responsibility
• English proficiency for daily communication

Nice to have:

• TimescaleDB
• Kafka
• Tableau

• Design, implement, and maintain data ingestion and processing pipelines
• Design, implement, and maintain data platforms in cooperation with the DevOps team
• Prepare data for reports and other processes
• Create, manage, and optimize data models
• Provide daily support to clients from Energy, Utilities, and Manufacturing sectors