The Data Engineering Market Report 2025 provides an overview of the industry’s landscape, emphasizing trends and developments shaping the industry. Organizations increasingly depend on data-driven decision-making, driving demand for efficient data management and processing solutions. The advancements in big data, IoT, and AI integration contribute to this growth. The report explores key trends such as reducing data silos, adopting cloud-native technologies, and integrating AI-driven automation to streamline processes and enhance operational efficiency.
This data engineering report serves as a reference for stakeholders within the industry, investors, policymakers, and economic analysts, providing a snapshot of the industry’s health to map its trajectory for innovation and growth in the coming years.
StartUs Insights Data Engineering Market Report 2025
- Executive Summary
- Introduction to the Data Engineering Report 2025
- What data is used in this Data Engineering Report?
- Snapshot of the Global Data Engineering Industry
- Funding Landscape in the Data Engineering Industry
- Who is Investing in Data Engineering Solutions?
- Emerging Trends in the Data Engineering Industry
- 5 Innovative Data Engineering Startups
Executive Summary: Data Engineering Market Outlook 2025
This report is created using data obtained from the Big Data and AI-powered StartUs Insights Discovery Platform, covering more than 4.7 million global companies, as well as 20K+ technologies and emerging trends. We also analyzed a sample of 1500+ data engineering startups developing innovative solutions to present five examples from emerging data engineering industry trends.
- Industry Growth Overview: The data engineering industry has experienced a growth of 22.89% in the last year, with 1500+ startups and over 3000 companies driving innovation.
- Manpower & Employment Growth: The sector employs over 150000 professionals, with 20000 new jobs added last year
- Patents & Grants: Data Engineering holds over 60 patents and has secured more than 100 grants, emphasizing its intellectual property and financial support.
- Global Footprint: Leading hubs include the US, India, UK, Germany, and the Netherlands, with key city hubs in London, Bangalore, New York City, San Francisco, and Pune.
- Investment Landscape: The sector has seen over 450 funding rounds, with 170+ investors supporting over 190, contributing to a vibrant financial ecosystem.
- Top Investors: Infosys, Recognize Partners, Hinduja Global, and more collectively invest over USD 400 million in the industry.
- Startup Ecosystem: Five startups—deX (Data Lake Platform), PurpleCube AI (Gen AI Embedded Data Orchestration), Quantaleap (Cloud-based Data Engineering), IOblend (Real-time Data Integration), and Polypheny (Multi-Model Data Management)—showcase the sector’s global reach.
- Recommendations for Stakeholders: Industry stakeholders should prioritize scalable data infrastructure, integrate AI-driven automation, and address data quality to enhance operational efficiency and maintain a competitive advantage.
Explore the Data-driven Data Engineering Report for 2025
The Data Engineering Report 2025 uses data from the Discovery Platform and encapsulates the key metrics that underline the sector’s dynamic growth and innovation. The heatmap highlights key metrics, including 1500+ startups and over 3000 companies in the database. In the last year, the industry experienced a growth rate of 22.89%, supported by over 60 patents and more than 100 grants.
The global workforce in data engineering exceeds 150000 employees, with last year’s growth adding over 20000 professionals. The top five country hubs driving this industry are the US, India, the UK, Germany, and the Netherlands. Leading city hubs include London, Bangalore, New York City, San Francisco, and Pune, showcasing regional innovation centers.
What data is used to create this data engineering report?
Based on the data provided by our Discovery Platform, we observe that the data engineering industry ranks among the top 5% in the following categories relative to all 20K topics in our database. These categories provide a comprehensive overview of the industry’s key metrics and inform the short-term future direction of the industry.
- News Coverage & Publications: The data engineering industry received significant attention, with over 8200 publications in the last year.
- Funding Rounds: With more than 450 funding rounds recorded in our database, the sector shows increasing financial activity.
- Manpower: Employing over 150,000 workers, the industry added more than 20000 new employees last year.
- Patents: The industry holds over 60 patents, highlighting intellectual property strength.
- Grants: Over 100 grants have also been awarded to this sector.
- Yearly Global Search Growth: The industry’s yearly global search growth of 19.53% further emphasizes its strong presence.
A Snapshot of the Global Data Engineering Industry
The data engineering industry shows a growth rate of 22.89% in the last year, with over 1500 startups driving innovation. Among these startups, more than 130 are in the early stage, and over 80 have engaged in mergers and acquisitions (M&A). The industry holds over 60 patents from over 55 applicants, increasing at a rate of 3.84% annually. Moreover, China and the USA lead in patent issuance, with more than 20 and 15 patents, respectively.
Explore the Funding Landscape of the Data Engineering Industry
The sector sees an average investment value of USD 7 million per round across more than 450 funding rounds. Over 170 investors support 190+ companies, highlighting the sector’s potential for continued growth.
Who is Investing in Data Engineering?
The top investors in the data engineering industry have invested over USD 400 million, supporting innovation and growth.
- Infosys invested USD 114.4 million in at least one company.
- Recognize Partners has contributed USD 100 million to at least one company.
- Hinduja Global allocated USD 58.8 million to at least one company.
- LBC Credit Partners contributed USD 55 million to at least one company.
- Y Combinator invested USD 1 million across three companies.
Access Top Data Engineering Innovations & Trends with the Discovery Platform
Explore the emerging trends within the data engineering landscape including the firmographic data:
- Large Language Models (LLMs) have become a key trend in data engineering, with over 1800 companies in this space. These companies employ more than 90000 professionals, including 15000 new hires in the last year. The annual growth rate for LLMs is 103.37%, indicating their increasing use for advanced data engineering tasks, such as natural language processing and AI-driven data analysis.
- Cloud-based Data Engineering is another trend, with over 400 companies employing more than 40000 individuals. The trend continues to grow, with 8000 new employees added last year and an annual growth rate of 17.02%. This shift highlights the move towards scalable and flexible cloud-based solutions in data management and processing.
- Data Lakehouse technology is also emerging as a significant trend, with over 140 companies and 7000 employees. This trend has gained momentum, adding 1000 new employees last year, and has an annual growth rate of 55.92%. It reflects the increasing adoption of unified platforms for managing large volumes of structured and unstructured data.
5 Top Examples from 1500+ Innovative Data Engineering Startups
The five innovative startups showcased below are picked based on data including the trend they operate within and their relevance, founding year, funding status, and more. Book a demo to find promising startups, emerging trends, or industry data specific to your company’s needs and objectives.
deX offers a Data Lake Platform
Brazilian startup deX offers deX Lake, a platform to streamline data engineering. The platform integrates data ingestion, transformation, orchestration, and monitoring within a single interface. This simplifies complex processes through a serverless infrastructure. Its key features include over 300 native data connectors, automated data testing, and continuous integration, accessible through a browser-based IDE. deX reduces operational overhead and enables businesses to focus on deriving actionable insights from data, enhancing decision-making, and driving growth.
PurpleCube AI builds Gen AI Embedded Data Orchestration Platform
US-based startup PurpleCube AI develops a data orchestration platform that integrates Generative AI into the data engineering process. This platform automates data pipelines, optimizes data flows, and generates insights by utilizing a combination of data ingestion, transformation, and quality assurance functions. With features such as a no-code drag-and-drop interface, active metadata, and a choice of processing engines, PurpleCube AI offers orchestration across various data workloads. The startup supports all data types, from structured to unstructured, and enables organizations to manage analytics, machine learning, and AI within a single platform.
Quantaleap enables Cloud-based Data Engineering
Dutch startup Quantaleap offers a cloud-based data engineering platform that combines DevOps with data science to enhance IT operations across multiple cloud environments. The platform analyzes and cross-references monitoring data using machine learning, providing customized insights into cloud operations, including threat identification and incident prediction. These insights are then integrated into automated workflows, allowing cloud services to adapt based on unusual patterns, thereby improving scalability and efficiency. By transforming operations into digital blueprints and providing observability-as-code, Quantaleap enables organizations to streamline complex IT tasks, ensuring sustainable and efficient cloud management.
IOblend supports Real-time Data Integration
IOblend, a UK-based startup, provides a data integration platform with built-in DataOps capabilities. The platform simplifies and automates data flow across different environments. It handles both batch and low-latency streaming data, making it suitable for complex integrations, IoT analytics, and AI initiatives. The startup leverages Apache Spark and enables rapid development of production-grade data pipelines, reducing manual effort and development costs. The platform also supports various data architectures and integrates with data sources like AWS, Azure, and Snowflake. IOblend accelerates data integration projects, streamlining the data management process and aiding companies to achieve faster ROI.
Polypheny facilitates Multi-Model Data Management
Swiss startup Polypheny provides a multi-model data management system that integrates relational, document, and graph data models into a unified platform. This allows businesses to execute cross-model queries and manage heterogeneous data from various sources. The startup’s system supports multiple query languages, including SQL, MongoQL, and Cypher, enabling data retrieval and manipulation across different data types. It also includes scalable and efficient storage, query optimization, and the ability to handle mixed workloads, making it suitable for data-intensive applications such as data analytics, machine learning, and data integration.
Gain Comprehensive Insights into Data Engineering Trends, Startups, or Technologies
In 2025, the data engineering industry will see more automation and the adoption of AI-driven tools to optimize data management processes. Trends like real-time data integration, multi-cloud strategies, and the rise of DataOps practices will shape the industry, allowing organizations to manage complex, large-scale data more efficiently. Get in touch to explore all 1500+ startups and scaleups, as well as all industry trends impacting data engineering companies.
