High-Impact Data Engineering

Transform raw data into strategic insights through engineering.
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Gain actionable insights, make informed decisions

Data engineering helps you get the most out of your data, ensuring scalability and reliability. Here's how we help.
  • Solid data architecture. We implement a scalable data architecture that ensures data is collected, integrated, validated, and delivered to key stakeholders.
  • Scalable data platform. We create platforms to store and process large volumes of data, facilitating smooth data flow, and supporting real-time analytics.
  • Robust data pipelines. Our team designs data pipelines that consolidate information from various sources, enabling analytics, visualizations, and actionable insights.
  • Long-term data strategy. We work with you to develop a scalable, data-driven strategy that adapts to increasing data volumes, ensuring long-term success.

Why seek support with data engineering?

Businesses we’ve worked with reported: improved data accessibility, faster decision-making with real-time insights, and scalable data infrastructure, even with limited resources. We optimized data strategies for:

In our clients' words

We partnered with a client in intelligent energy management to develop a prototype for forecasting and visualizing complex data.
  • The partnership allows us to build a best in class product.
    Leroy NeedEnergy

    Leroy T. Nyangani

    Co-Founder and Team Lead at NeedEnergy

60% more engagement with hyper-personalization

Netguru developed an AI-powered solution for Newzip, a real estate-as-a-service platform, to drive hyper-personalized user experiences. The proof of concept integrated customer data to provide tailored insights, enhancing interactions between home buyers, agents, and lenders.

This resulted in a 60% increase in engagement and a 10% boost in conversions, confirming that personalized experiences can effectively drive user engagement and platform loyalty. The solution was scalable, handling more than 10,000 users nationwide.

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Newzip case study new1

Speeding up Merck’s process from 6 months to 6 hours

Merck wanted to reduce the manual effort of identifying chemical compounds from scientific literature. We implemented an AI-powered R&D Assistant to automate data extraction and analysis.

Within just 5 weeks, we delivered a proof of concept hosted on Merck’s secure AWS infrastructure, utilizing their own GPT service. The AI solution reduced the process from 6 months to a mere 6 hours, drastically improving efficiency and freeing experts to focus on strategic tasks.

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RnD lab: AI Assistant

Top challenges we solve

  • Inefficiencies. For Libra, we streamlined the time-consuming process of manual data labeling by creating a platform that delegates annotation tasks to users.
  • Poor data quality. For CLARIN-PL, we built a high-quality dataset of valid and abusive clauses from real documents, enabling the NLP model to accurately classify and differentiate between them.
  • Scalability with big data. For NeedEnergy, we used AWS and Docker to create a scalable platform that improves energy predictions as data grows.

Why Netguru?

  • 15+

    Years on market
  • 400+

    People on board
  • 2500+

    Projects delivered
  • 73

    Our current NPS score

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Check how we delivered tangible gains for clients across industries.

Fuel business growth with streamlined data engineering solutions

As businesses face growing pressure to optimize processes and cut costs, a well-structured data strategy becomes crucial. By implementing scalable data architectures and pipelines, you create a foundation that enhances operational efficiency. This approach not only reduces initial infrastructure costs but also ensures that your data is reliable, accessible, and ready for analysis—driving informed decisions and sustainable business growth.

What are Data Engineering Services?

Netguru's Data Engineering services are designed to help businesses optimize their data usage, management, and automation. We create advanced data pipelines, enabling you to focus on extracting valuable insights without the complexities of manual data handling. Our expert team works with global enterprises to develop sophisticated data processing systems, extract critical business information, and ensure the highest standards of data quality and availability.

How does Netguru support clients in Data Engineering?

Our Data Engineering practice specializes in designing and constructing robust systems for data ingestion, collection, storage, and analysis. We facilitate seamless access to data, perform sophisticated analyses on raw data, and develop advanced Data Pipelines and Data Platforms. By leveraging cutting-edge technologies and methodologies, we ensure that data is both accessible and actionable, empowering companies to make informed decisions.

Who are Netguru's Data Engineering consultants?

Netguru's Data Engineers are experts in various programming languages essential for data platform development. They build data pipelines for seamless data transfer between systems, handle data transformation, and ensure data is consistently available, properly formatted, and ready for complex analytical processes. Their work is crucial for integrating disparate data systems and fostering data-driven decision-making across organizations.

How do big tech companies use data engineering?

Big tech companies leverage data engineering to create value for their businesses. For example, e-commerce giants use data to personalize customer interactions, optimize pricing and advertising, improve supply chain management, and reduce fraud. Some companies even use data engineering to study customer behavior and optimize personalized experiences.

What's the difference between Data Engineering and Data Science?

While Data Science focuses on analyzing organized and unstructured data to provide useful insights, Data Engineering is responsible for creating pipelines or procedures to transport data from one instance to another. Data Engineering builds the foundation that Data Science relies on for analysis.

Why is Data Engineering so important?

Data Engineering is crucial for establishing an effective analytics program. It builds a solid foundation for data management, identifies gaps and quality issues, and improves data collection. Companies that invest in data engineering expertise are better positioned to leverage their data effectively in the coming years.

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Let's see how we can help you optimize your business.

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