Data Engineering

Modern Data Pipelines and Cloud Data Platforms

We build the pipelines, warehouses and lakehouses that turn raw data into analytics-ready assets, and migrate legacy systems to the cloud.

PipelinesGoogle CloudAzureSnowflakeMigration
Data Engineering at Upen Group: Data pipelines: glowing tubes carrying light particles from frosted glass source blocks through transformation gears into a cloud data warehouse tower
Overview

Experts in Cloud Data Engineering

Data engineering is the practice of designing and building systems that collect, store, transform and serve data for analytics, reporting and machine learning. Upen Group specializes in data analytics solutions on modern cloud platforms.

Adopting the latest cloud data technologies drives advanced capabilities in data management, analytics and machine learning, with the performance and cost reductions business leaders seek. Our automated migration tooling moves legacy systems to platforms such as Google Cloud quickly and cost-effectively.

Our team of cloud architects and big data engineers delivers projects for clients across industries, with every pipeline validated before it reaches your dashboards.

Capabilities

Data Engineering Services

Data Pipeline Development

Batch and streaming pipelines that ingest, transform and deliver data reliably.

Cloud Data Warehouses

Design and build on Google BigQuery, Azure and Snowflake for fast, scalable analytics.

Legacy Data Migration

Move warehouses, Hive and Hadoop workloads and databases to the cloud with automated tooling.

Data Modeling

Analytics-ready models that make data easy to query and understand.

Real-time Data

Streaming architectures for live dashboards and event-driven applications.

Analytics & ML Enablement

Clean, governed datasets that feed BI tools and machine learning models.

Our methodology

The HIVE Methodology

A proven four-stage approach for migrating and modernizing data platforms with confidence.

01

Holistic Study

Understand your data landscape, sources, consumers, quality issues and business goals before anything moves.

02

Integration

Design and build pipelines that bring data together on a modern, governed platform.

03

Validate

Reconcile and test data against source systems so every report can be trusted.

04

Enhance

Optimize performance and cost, and add analytics and machine learning on the new foundation.

FAQ

Frequently Asked Questions

Still have questions? Our team replies within one business day.

Contact Us →
What is the Google Cloud Platform?
Google Cloud Platform (GCP) is a suite of cloud computing services that businesses, IT teams and developers use to work more efficiently, gain flexibility and build data, analytics and AI solutions.
How do I migrate to Google Cloud?
Migrating a data warehouse is rarely a one-step task. It is typically a phased journey: assess sources and dependencies, migrate schemas and pipelines in waves, validate results against the source, then optimize and retire legacy systems.
What does a data engineer do?
A data engineer designs and builds the pipelines, storage and models that make data available, reliable and ready for analytics and machine learning.
Do you work with Snowflake and Azure as well as Google Cloud?
Yes. We build and migrate data platforms on Google Cloud, Microsoft Azure, Snowflake and AWS.

Ready to Modernize Your Data Platform?

Tell us where you are today and what you want to achieve. We will come back within one business day with next steps.

Talk to an Expert →
+1 469-333-7815
Mon–Fri, 9 am–5 pm CT
4322 N Beltline Rd, Suite B214
Irving, TX 75038

Last updated: October 2, 2026