Streamline your data pipelines to support real-time decision-making capabilities. Deploy best practices across your Big Data stack.

  • Prototype Development

    An iterative approach through quick proof-of-concepts will help validate your Big Data innovations faster than a waterfall approach.

  • Repeatable Deployments

    Go from Jupyter Notebooks to Cloud-native containers. Automate the delivery of your pipeline using Continuous Integration/ Continuous Deployment (CI/CD). Prevent drift in your architecture using Infrastructure as Code (IaC) tools like Terraform.

  • Observability

    Improve your ability to troubleshoot issues, and find performance bottlenecks by adding instrumentation in your ETL process. Roll up the data into dashboards for real-time decision making.

  • Data Pipeline Optimization

    Simplify and modernize your data pipeline: move away from batch processing and implement real-time streaming into your data lake.

Technology Expertise

20+ years of software development and deployment experience with a focus on:

  • Python / Django / NodeJS
  • AWS / GCP / Azure
  • Databricks / Airflow
  • React / Angular
  • PostgreSQL
  • scikit-learn
  • Kubernetes / Terraform
  • Linux / FreeBSD

How to Work with Us

Flex 6 process diagram

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