Report

The Big Data Engineering Services Market size is estimated at USD 91.54 billion in 2025, and is expected to reach USD 187.19 billion by 2030, at a CAGR of 15.38% during the forecast period (2025-2030).

Application programming interfaces are necessary for data integration and engineering. Data engineers use specialized tools, procedures, and equipment to prepare and analyze data for later analysis.

Key Highlights
- The growth of the big data engineering services market has been driven by several key factors. Firstly, the exponential increase in data generation across various industries, fueled by the proliferation of digital technologies, has created a pressing need for advanced data management and processing solutions. As organizations seek to harness the potential of their data, they increasingly turn to big data engineering services to optimize storage, processing, and analysis capabilities.
- The financial industry is quickly changing and providing new consumer products and services. The banking industry is expected to significantly impact the data engineering market. For instance, the partnership between the National Australia Bank and Amazon Web Services has grown. According to the bank, 70% of its programs have now been migrated to the cloud, and it just became the first significant Australian bank to convert its online business banking platform.
- The amount of data used in healthcare is growing quickly. Electronic health records are the most prevalent significant data source in the healthcare industry. Earlier, this information was stored in handwritten files. Medical researchers can now create prediction models thanks to the enormous data created by EHRs and powerful analytics techniques like machine learning.
- Furthermore, advancements in machine learning and artificial intelligence have opened up new possibilities for extracting valuable insights from large datasets, prompting organizations to invest in data engineering services to support their AI initiatives. Additionally, regulatory requirements around data privacy and security have compelled companies to adopt more robust data management practices, leading to increased demand for specialized big data engineering expertise.
- Not comprehending the needs of a specific user group is difficult for a data engineering project. The endless influx of data and dealing with value inconsistencies can quickly become overwhelming. Establishing a thorough data management strategy with a data governance plan is one potential response to this data engineering challenge.


Big Data Engineering Services Market Trends

Big Data Analytics in Banking is Expected to Grow Significantly


- The banking industry has witnessed a significant surge in the adoption of big data analytics and engineering, primarily due to the immense value they offer in enhancing operational efficiency, customer experience, and risk management. Companies like JPMorgan Chase and Wells Fargo have invested heavily in big data initiatives to harness the vast amounts of data generated within their operations.
- Furthermore, big data engineering facilitates the processing, storage, and analysis of massive datasets, enabling banks to handle the velocity, variety, and volume of data efficiently. With technologies like Hadoop and Spark, banks can store and process data at scale, enabling faster decision-making and improved customer service.
- Moreover, the growth of digital banking and the proliferation of online transactions have further fueled the demand for big data solutions in the banking sector. By leveraging advanced analytics and machine learning algorithms, banks can offer personalized recommendations, streamline operations, and mitigate risks effectively.
- In December 2023, Union Bank of India partnered with Accenture to create a scalable and secure enterprise data lake platform. This initiative aims to enhance operational efficiency, provide customer-centric banking services, and improve risk management. The platform will leverage predictive analytics, machine learning, and artificial intelligence to generate valuable insights from structured and unstructured data. Additionally, it will empower employees with robust data visualization and reporting capabilities across various functions.


Asia-Pacific to Hold Major Market Share


- The big data engineering market in Asia-Pacific countries like China, Singapore, India, Malaysia, and others has experienced significant growth in recent years, driven by factors such as increasing adoption of digital technologies, rising demand for data-driven decision-making, and the proliferation of internet-connected devices. Companies in these regions are recognizing the value of harnessing vast amounts of data to gain insights and stay competitive in the global market.
- Key players like Alibaba and Tencent have been at the forefront of big data innovation, leveraging their extensive user bases and advanced analytics capabilities to offer personalized services and improve operational efficiency. For example, Alibaba's cloud computing arm, Alibaba Cloud, provides a range of big data solutions, including data warehousing, analytics, and artificial intelligence services, catering to businesses across various industries.
- Moreover, companies like Grab, a key super app in Southeast Asia, rely heavily on big data engineering to optimize their ride-hailing, food delivery, and financial services platforms. Grab utilizes data analytics to enhance user experiences, optimize driver allocation, and develop new products and services tailored to customer preferences, contributing to its rapid expansion and market dominance.
- Meanwhile, in Malaysia, companies like AirAsia are leveraging big data engineering to transform the aviation industry, offering personalized travel experiences and optimizing flight operations through predictive analytics and machine learning algorithms. AirAsia's data-driven approach has enabled it to streamline processes, reduce costs, and maintain a competitive edge in the highly dynamic airline market.
- Overall, the growth of the big data engineering market in Asia-Pacific countries reflects a broader trend toward digital transformation and innovation, with companies across various sectors harnessing the power of data to drive business success and unlock new opportunities for growth and differentiation in an increasingly competitive landscape.


Big Data Engineering Services Industry Overview

With new opportunities for differentiation and value-added services, the moderately fragmented big data engineering services market has the potential to change the competitive landscape. Moreover, many sectors are investing extensively in artificial intelligence, and there is a high demand for big data engineering technology and capabilities. In order to gain market share in the intelligence sector and expand the scope of their service offerings, well-known vendors, such as Accenture PLC and Capgemini SE, are making acquisitions and investments in new companies and technologies.


- October 2023: Onix, a Google Cloud partner, acquired Datametica, an IP-driven consulting firm specializing in data migration, modernization, and BI/analytics. Datametica's suite of proprietary products automates the migration and modernization of data warehouses, databases, ETL processes, and analytical workloads to Google Cloud, delivering faster results and guaranteed outcomes for customers. This strategic move enhances Onix's data and AI capabilities, positioning them as a leader in IP-driven solutions for cloud transformation and data management.
- February 2023: Alteryx introduced enhanced self-service and enterprise-grade features in its Alteryx Analytics Cloud Platform. The reimagined Alteryx Designer Cloud interface empowers modern data workers to profile, prepare, and pipeline their data interactively and collaboratively. Analysts and data engineers can now build interactive reports with ease, and Alteryx Auto Insights leverages machine learning to surface explanatory values and key drivers for better decision-making. The platform's scalability and security ensure that organizations can make faster and more informed decisions while maintaining data governance standards.


Additional Benefits:

- The market estimate (ME) sheet in Excel format
- 3 months of analyst support