Data Engineering & BI

Data Engineering & Business Intelligence Services

Build scalable data platforms that unify your data, streamline ETL pipelines, and transform raw information into real-time data analytics.

Build Your Data Infrastructure
Data platform connecting sources, storage, analytics and automation
70 %

of enterprise data goes unused

60 %

faster decision-making with real-time data

20 +

Years of Engineering Excellence

5 x

faster analytics with modern data platforms

Transform Raw Data into Actionable Business Insights

Five data engineering services that turn scattered data into a trusted foundation.

Service 01 of 05

Reliable Data Pipelines

Automating the flow of data from source to warehouse with 99.9% uptime.

  • Automated source-to-warehouse flow
  • 99.9% pipeline uptime
  • No manual exports in the loop
Service 02 of 05

Unified Truth

Eliminating data silos to create a single, authoritative source for all business metrics.

  • Data silos eliminated
  • One authoritative source
  • Consistent business metrics
Service 03 of 05

Actionable Visualization

Transforming complex datasets into intuitive, interactive dashboards that anyone can understand.

  • Complex datasets made intuitive
  • Interactive dashboards
  • Readable by non-technical teams
Service 04 of 05

BI & Dashboards

Transform complex data into interactive BI dashboards and visual reports. Empower teams to monitor KPIs and make faster, data-driven decisions.

  • Interactive BI dashboards and reports
  • KPI monitoring for every team
  • Faster, data-driven decisions
Service 05 of 05

Real-Time Analytics

Process and analyze data in real time to gain immediate insights. Enable faster responses to changing business conditions and opportunities.

  • Real-time processing and analysis
  • Immediate insights, not overnight
  • Faster response to changing conditions
Closing Step

Explore Data Engineering Solutions

Talk to a data engineering expert before the dashboards get built.

Talk to a Data Engineering Expert
Trusted partners

The platforms and clients we build with

Certified across the major clouds and trusted by enterprise teams to deliver AI that reaches production.

Modern Data Architecture for Scalable Analytics

Build a unified data platform that collects, processes, and transforms data into actionable insights across your organization.

1 Data Sources
2 Data Ingestion
3 Data Processing
4 Data Storage
5 Analytics & BI
01 of 05 · Data Sources

Collect data from multiple sources such as applications, databases, APIs, and third-party platforms.

02 of 05 · Data Ingestion

Capture and move data through scalable pipelines using batch and real-time processing.

03 of 05 · Data Processing

Clean, transform, and prepare raw data for analytics and reporting.

04 of 05 · Data Storage

Store structured and unstructured data in modern data warehouses and lakes.

05 of 05 · Analytics & BI

Turn processed data into insights through dashboards, reporting, and analytics tools.

Measure the Difference

Faster Decision Making

Reduce reporting cycles from weeks to real-time, increasing operational agility.

Cost Efficiency

Optimize cloud storage and compute costs, reducing data infrastructure spend by up to 30%.

Data Integrity

Eliminate manual errors and "Excel-hell" with automated, validated pipelines.

Better Forecasting & Planning

Use reliable data and analytics to forecast trends, plan resources, and anticipate demand more accurately.

Scalable Data Infrastructure

Build modern data platforms that grow with your business and support increasing data volumes.

Democratized Access

Empower non-technical teams to answer their own questions through self-service BI.

Data Engineering & Analytics Technology Stack

We leverage modern data platforms, analytics tools, and cloud technologies to build scalable and high-performance data ecosystems.

AI & Data

  • Python
  • FastAPI
  • Apache Spark
  • PostgreSQL
  • MongoDB
  • Redis
  • Sequelize
  • MySQL

Cloud & devOps

  • Azure
  • AWS
  • Docker
  • Kubernetes
  • GitHub Actions

Backend

  • React
  • Next.js
  • Node.js
  • Java
  • PHP
  • Laravel
  • Ruby
  • Ruby on Rails
  • GraphQL

Frontend

  • React
  • Next.js
  • Vue.js
  • Angular
  • TypeScript
  • JavaScript
  • HTML5
  • CSS3
  • jQuery

UI & Platforms

  • Tailwind CSS
  • Material UI
  • Bootstrap
  • WooCommerce
  • Redux
  • Figma
  • Unity
  • WordPress
  • npm

Our Approach to Building AI Solutions

We follow a structured approach to design, develop, and deploy AI solutions that integrate seamlessly with your existing systems.

1 Architecture Audit
2 Schema Design
3 Pipeline Construction
4 Dashboard Deployment
5 Optimization & Monitoring
01 of 05 · Architecture Audit

We evaluate your current data sources, quality, and business requirements.

02 of 05 · Schema Design

Modeling the data for performance — choosing between Star, Snowflake, or Data Vault schemas.

03 of 05 · Pipeline Construction

Engineering the ingestion and transformation layers with a focus on observability.

04 of 05 · Dashboard Deployment

Designing the frontend visualization layer and training your team on self-service tools.

05 of 05 · Optimization & Monitoring

Continuously improve performance, reliability, and data quality.

In Their Words

Trusted by enterprise leaders

What decision-makers say about working with Techverx.

5 stars

We worked with Techverx on the development of an application. Their team took on the task as though it was being developed for themselves. Their expertise, support and contributions were very key to the success. Techverx continues to be involved in further development for our company. I highly recommend their services.

Barbara Roscher Director Information Technology — Postal Methods
5 stars

We reached out to Techverx in March 2019 and asked them to provide us with a proof of concept for a new subsystem that we were building. They rose to challenge and delivered a great POC in the four week timeframe. Since, that time Techverx has been a great partner for us. They are an integral part of both our architecture and development teams.

David Gay Head of Engineering — Lightpoint
5 stars

Working with Techverx has been a great collaboration is more than an understatement. They are engaging, interactive and futuristic. The inhouse support is always there around the clock to keep us updated about the process.

Sam Kahanov Head of Product Management — Drive
5 stars

Techverx got us from a stuck pilot to a governed production system in a single quarter — they understood compliance as well as engineering.

Richard General Manager — Subway
Case Studies

Recent work, from concept to production

A look at systems we've designed, built, and shipped — with the outcomes they moved.

Sharkfin
View Story
Case Studies

Modern FinTech Infrastructure for Trading and Operations

SharkFin is a cloud-based SaaS platform for hedge funds, family offices, and financial institutions, providing integrated trading, portfolio, risk, compliance, analytics, and operations capabilities.

60 %
Faster release cycles
45 %
Improved platform performance
5 X
Transaction-volume capacity
BMO Financial Group
View Story
Case Studies

Future-Ready Banking Infrastructure for BMO Financial Group

BMO Financial Group is one of North America's leading financial institutions, serving millions of customers through a wide range of banking and financial services.

13 M+
Customers served globally
100 %
Migration from Silverlight to Angular
40 %
Faster Load Time
Quure
View Story
Case Studies

A SaaS based telehealth platform for clinics

Quure is an innovative telehealth platform designed to unify complex healthcare services through a single interface. It integrates EMR, chronic disease management, and pharmacy tools.

400 +
Users onboarded in first 60 days
13
Active microservices for modular scalability
99.9 %
High-speed, reliable system uptime
FAQ

Frequently asked questions

The answers to your questions about data engineering and BI.

Data engineering is the practice of building pipelines, warehouses, and infrastructure that collect, clean, and prepare data so it can be used for analytics, reporting, and machine learning.

Data engineering builds the pipelines and infrastructure that move and clean data. Business intelligence uses that data to create dashboards, reports, and insights for decision making.

Data engineering projects typically range from $30,000 for a focused pipeline build to $250,000 or more for a full enterprise data platform.

ETL stands for extract, transform, load, the process of pulling data from source systems, cleaning it, and loading it into a data warehouse where it can be analyzed.

Yes. Business intelligence consulting is a core part of the Data Engineering and BI service, covering dashboard design, KPI definition, and reporting infrastructure.

A data warehouse is a centralized system for storing structured data from multiple sources. Companies that need consistent, fast reporting across departments typically benefit from one.

A focused ETL pipeline typically takes 4 to 8 weeks. A full data platform with warehousing and BI dashboards usually takes 3 to 6 months.

Yes. Data quality and cleanup services identify inconsistencies and standardize data before it is used for analytics or AI.

Techverx works with modern data engineering frameworks and BI tools, selecting the right stack based on data volume, existing systems, and reporting needs.

In most cases, yes. Clean, well-structured data is the foundation AI models need to perform accurately, which is why data engineering often comes before AI development.