P L E A S E  W A I T...
Data Engineering



Nabler produces highly scalable and economical Big Data Engineering solutions. We provide Data Engineering services that deliver business value to digital marketing across industries.
  • Trained and certified resources across AWS, GCP, Azure, and SFMC.
  • Pod structure that offers a combination of skill sets required for any project.
  • Data Engineers who are experts in marketing, advertising, and e-commerce analytics.
  • Starter sets and pre-configured stubs that reduce time to market.

Data Engineering Challenges

Ignoring zero latency

Adaptability to changing data sources and maintenance of source nomenclature, quality, and trust.

lack of skill

Unable to manage numerous databases and different programming platforms.

lack of expertise

Unsure of how to navigate the cloud adoption journey in an expanding, multi-cloud environment.

not able to maximize

Loss of customer experience because of poorly optimized data applications.

Nabler’s Data Engineering Services


Increase data trust through superior definitions and well-maintained data integrity, usability, and reliability.


Reduce overheads and project risks through end-to-end skills and work management by a single vendor.


Accelerate cloud migration and adoption through multi-cloud and multi-tech service delivery and partnerships.


Optimize operational cost through application scaling and continuous monitoring.

What We Do in Data Engineering

data ingestion
Data Ingestion through Connectors

Ingestion of all types of data and databases onto data lakes and data warehouses to make decisions quicker and easier with current, consistent data. These connectors are generally deployed in cloud platforms using tools like AWS Lambda, GCP Cloud Functions, Azure functions, etc.

Data Pipeline on The Cloud

High performance data pipelines using AWS Glue, GCP Dataflow, or equivalent, to automate data validation, transformation, and unification processes. These connect popular data lakes including AWS S3, GCP Cloud Storage, Azure Blob Storage with equivalent data stores such as BigQuery, AWS Redshift, etc.

data quality
Data Quality Management

Maintain a data health check at ingestion time to score and identify bad data sources as well as data refresh and augmentation to prevent data quality depreciation over time

building 36 degree data views
Build 360-degree Data Views

A comprehensive view of customers, products, channels, and campaigns, deployed in platforms like BigQuery, MS SQL, AWS RDS etc. Integrate different analytics and AI/ML applications like AWS Sagemaker, Azure Databricks, GCP Vertex etc.

high performance
Scalable Data Application Deployment

MVC architecture-based, enterprise grade, and low-latency cloud applications that leverage options including MongoDB NoSQL databases, Neo4J graph databases, and PostgreSQL Redshift databases.

Why Nabler

single pod

A highly skilled team of engineers certified across multiple clouds and MarTech.

proven track record

Proven business Use Cases from an array of industries using clouds like AWS and GCP .

reusable connectors

Reusable connectors compatible with a wide variety of marketing, advertising, and e-commerce platforms.

proven track record

Data governance, output quality control rigor, and workload automation and optimization.

Articles and Case Studies

Our Partners

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Want to learn more? Let’s talk