We build Data Engineering, BI, and AI/ML solutions to support your strategic digital transformation initiatives.
Our technical team has sound experience with the wide spectrum of modern technologies and tech stacks. We bring to the table
- BigData engineering experience (Spark, Apache Airflow)
- Experience building BI and Data infrastructure solutions in cloud
- Google Cloud Platform (BigQuery, DataFlow, Google Composer, Dataproc, Metabase, DataPrep, cloud functions, GCS etc.)
- Amazon WS (S3, Glue, Athena, Redshift, Sage, EMR services, lambda functions, managed database instances etc.)
- Azure (Azure SQL, OLAP, Cosmos Databriks etc.)
- Proven record of successful projects in building data integration and Airflow-powered workflow automation and ETL solutions to collect data from various cloud / Web API-based data sources (Google Analytics, Google AdWords, Facebook, Mixpanel, OpenExchangeRates, LeadSquared, Salesforce, ERPNext etc.)
- Sound experience with Python-based machine learning algorithms and tools (time series, regressions, bagging, decision trees, random forests, SVM, gbm, adaboost, xgboost, old-generation neural networks, deep learning; ensembles of different machine learning models etc.)
- Specific expertise with Deep Learning algorithms implemented in Tensorflow, Keras and H2O.ai platforms
- RDBMS Development and DBA (MySQL/MariaDB, PostgreSQL, Sybase, Oracle, MS SQL Server/Azure SQL)
- Seasoned experience with various BI platforms and tools (Power BI, QlikView, QPR, Tableau, MS SSAS)
- Experience with NetOps/DevOps on complex enterprise platforms and heavy loaded cloud-based online services (docker and Kubernetes containers etc.)
- Experience developing System and Solution Architectures for modern high-performance distributive solutions, both cloud-based and on-premise ones
- Seasoned project management skills using both traditional and agile methodologies, using modern project management and SDLC systems (Atlassian suite – Jira, Confluence, FishEye, Bamboo etc.; ScrumDo, Trello, Harvest, Asana, Assembla, DokuWiki etc.)