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Data Engineering


Data-driven businesses depend on accurate, timely, and reliable data. We set up and optimize data management capabilities to support the whole data cycle. This includes data generation and sourcing, integration of various data sources, and aggregation in data lakes and data warehouses. We specialize in setting up, maintaining, and optimizing various tools and components to implement this cycle. Based on our rich experience in this field, we ensure great performance and data quality at every phase of this process.



Analyze and design

  • Analysis of the current scenario and data sources
  • Designing the target architecture and the data model

Plan and implement

  • DWH/data lake implementation planning and initial setup
  • Data integration procedures
  • Data cleansing procedures
  • Defining the migration plan
  • Data import


  • Performance monitoring
  • Evaluation of improvements
  • Optimization procedures


We leverage a mix of industry standards and proprietary accelerators for automation, risk mitigation and velocity.

Data Ingestion and ETL tools

Pentaho Kettle, Talend, Google Cloud Data Fusion, Apache Airflow, Apache Beam, Kafka, Spark, Python.

Data Storage and Data Management tools

Google BigQuery, MongoDB, PostgreSQL, Oracle,  Cloudera, Google Cloud Storage, Pentaho, Talend, DataPrep. 

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