Data Engineering

Our industry experience and advanced data engineering solutions can get you started on your digital journey.

Don’t just upgrade, transform the business process.

Improve your company's processes and operations through data management.

We help organization overcome data challenges and flourish in the global market.

Accelerate > Innovate > Transform

A team of highly-skilled and experienced Data Engineers and Consultants will help you optimize your data and create high-performance infrastructure to achieve your business goals and make better decisions.

Process Mining

Install our process discovery tools coupled with mapping techniques. With extensive experience in Measuring the manual effort end-to-end, Identifying the RPA and automation potential, Optimising sales channels and working capital, Implementing the transformed New GL, Improving quality and customer satisfaction.

SAP Migration

Understand the Know-How, Develop the To-be and Monitor business efficiency. Acquire top-down insights, perform a gap analysis to test new design; Monitor the adoption rates and global conformance with migration design, Respond immediately to unexpected process loops and other deviations.

Automation Roadmap

Lead the complete project of process automation with our expertise of techno-functional experience. Identify automation opportunities - prioritization Accelerate Implementation – Agile Create follow-up project enhancements - Sprints.


Improve speed, productivity, and quality with our process reengineering solutions.

We help redesign your business processes with the help of automated solutions and integrations


The client wanted to improve their vendor management procedures by building a centralized data management & Data Lake to execute analytics projects stored in the Data Lake, starting with depicting the procurement spend analysis (direct and indirect). They wanted a flexible data lake that would allow adding more sources in the future.


Carbynetech successfully integrated Supply-Chain transactions and Digital manufacturing transactions into a centralized data lake. Insights such as Material movements, Inventory postings, Stock transfers to Depots and warehouses, Manufacturing replenishment plans, Real-Time asset performance and Production stats were provided. Modelled storage process and built quality control for Data Lake Executed analytics to ensure business consumption through dashboards.


Built a Data-ops and Data Analytical Solution for a FMCG Manufacturing Company which streamlined and the dataflow from multiple sources, created a standard business workflow, transformed, and cleansed data so that client can make better decisions. Client faced challenges in making data accessible on-time, without costs, delays, and data quality issues. Local copies of data scattered in the ecosystem made the data unreliable and increased storage costs. Data delivery to consumers on- time had to wade through long request queues. Lack of skillsets to derive insights from data further added to data complexity issues


Setting up a central Cloud-Data warehouse as a single source of truth Laying the foundational data architecture that classified requests into zones based on repeatability and use Implementation of a metadata-driven governance system focused on UI to capture datarequests Building re-usable frameworks to enable the platform to serve personas with data requests, platform usage requests and insights requests Harnessing the power of Data-Bricks on Azure to create a dynamic, auto-scalable ingestion layer based on workload