Data Data Everywhere Oh! for a drop of sense!

Our experts help you and your team to control, organize and understand your data quickly. We use tools that are easy to setup, run and maintain. 

Why is Data Engineering important?

The digital transformation is happening at rapid pace. Unimaginable amount of data is being produced at ever higher velocity. Before we can understand  the data, we need  to organize, ensure quality,  consistency and security of data. 

Business decisions based on basic MIS or deep learning using ML/AI can only happen on a strong platform of readily available data. We provide you with right expertise in the field of Data Engineering. 

Data Visualisation

Data Pipeline Automation

Technologies in Data Engineering

Our experts help build right pillars for your Data infrastructure and we help train your team to maintain and expand the productivity.

Databases

MySQL, Postgres, Oracle
BigQuery, Redshift, Snowflake
MongoDB, CosmosDB DynamoDB

Programming Languages

Java
Python
SQL

Cloud Services

Microsoft Azure 
Docker
Amazon Web Services(AWS)

Orchestration

Airflow
Glue
NiFi

CI/CD Services

Git Actions
Jenkins
Code Pipeline

Testing/Quality

PyTest
JUnit
SonarQube

Infrastructure as Code

Terraform
Cloud Formation
Ansible

ETL

Spark
Python
SQL

Skills and Capabilities

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What data engineering services include?

We cover all aspects of data engineering at Madgical. Our experts work with your team to create and run you data pipelines.

Why work with us?

Madgical brings expertise in Data Engineering. We will help you choose the right technology and architecture. We will help you create the right team, trained in right processes to deliver quality in quick time.

Our model is to work with you to establish processes quickly, train in-house engineers to continue and grow the Data Engineering practice and augment talent from our pool as required.

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Ready to get started?

Drop a message and we are always happy to answer any questions, discuss our model or just expand our horizons over some coffee.