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Report Description

Report Description

Forecast Period

2027-2031

Market Size (2025)

USD 71.98 Billion

CAGR (2026-2031)

11.34%

Fastest Growing Segment

Small & Medium-Sized Enterprises

Largest Market

North America

Market Size (2031)

USD 137.13 Billion

Market Overview

The Global Big Data and Data Engineering Services Market will grow from USD 71.98 Billion in 2025 to USD 137.13 Billion by 2031 at a 11.34% CAGR. Big Data and Data Engineering Services encompass the architectural design, infrastructure development, and pipeline management required to transform raw, massive datasets into structured formats for analytical utilization. The market is primarily propelled by the exponential accumulation of unstructured data across digital ecosystems and the critical imperative for enterprises to operationalize real-time intelligence for competitive advantage. According to 'NASSCOM', in '2024', global investments in AI and data analytics sectors approached USD 83 billion, following a compound annual growth rate of 24% since 2019, reflecting the substantial financial commitment organizations are dedicating to these foundational technologies.

However, the expansion of these services faces a significant impediment regarding the complex regulatory landscape surrounding data privacy and sovereignty. The intricate nature of adhering to diverse jurisdictional laws creates friction in cross-border data governance, potentially stalling the scalability of engineering initiatives. This compliance burden, combined with the technical challenges of integrating legacy systems, continues to complicate the seamless deployment of global data strategies.

Key Market Drivers

The Integration of Artificial Intelligence and Machine Learning Technologies is fundamentally reshaping the market as enterprises transition from experimental pilots to full-scale production environments. This shift necessitates advanced data engineering services to build resilient pipelines, manage feature stores, and ensure high-quality data availability for complex algorithms. As organizations operationalize these technologies, the demand for MLOps and scalable infrastructure has surged to support the lifecycle of intelligent applications. According to Databricks, June 2025, in the 'State of Data + AI' report, the number of AI models registered for production increased by 1,018% year-over-year, highlighting the massive industrial pivot toward deploying functional AI assets and the subsequent need for engineering support.

Accelerated Adoption of Cloud-Based Data Architectures further fuels market expansion as businesses modernize legacy infrastructure to achieve greater agility and scalability. Companies are aggressively migrating workloads to public and hybrid cloud environments to leverage elastic computing power and unified analytics platforms. According to Flexera, March 2025, in the '2025 State of the Cloud Report', 78% of organizations reported focusing on the volume of workloads migrated to the cloud as a key metric, a significant rise from 36% in the previous year. However, this rapid decentralization often leads to complex fragmentation. According to Salesforce, in 2025, 90% of IT leaders indicated that data silos are creating significant business challenges, underscoring the critical need for engineering services to unify disparate systems.

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Key Market Challenges

The complex regulatory landscape regarding data privacy and sovereignty constitutes a substantial barrier to the expansion of the Global Big Data and Data Engineering Services Market. As nations enforce divergent data localization mandates and privacy statutes, organizations encounter severe restrictions on cross-border data flows. This legal fragmentation forces enterprises to abandon unified, efficient global data architectures in favor of segregated, region-specific infrastructures to ensure data residency. Consequently, engineering teams must manage disjointed pipelines, which drastically increases operational complexity and diminishes the analytical value derived from centralized, massive datasets.

This compliance burden necessitates the diversion of critical financial and technical resources toward legal governance and risk mitigation rather than engineering innovation or service scalability. The uncertainty inherent in navigating these shifting jurisdictional laws creates a cautious operational environment, causing firms to delay large-scale data initiatives. According to the 'International Association of Privacy Professionals', in '2024', only '20%' of privacy professionals expressed complete confidence in their organization's ability to maintain compliance with current regulatory standards. This pervasive lack of certainty directly hampers decision-making and stalls the adoption of global data engineering services, as organizations prioritize avoiding litigation and penalties over aggressive market expansion.

Key Market Trends

The Convergence of Data Lakes and Warehouses into Lakehouse Models is fundamentally restructuring the market by merging the low-cost storage of data lakes with the high-performance management capabilities of data warehouses. This architectural unification resolves the operational inefficiencies caused by fragmented data silos, allowing enterprises to run diverse analytical workloads on a single copy of data using open formats like Apache Iceberg. Consequently, organizations are abandoning complex, brittle ETL processes in favor of direct data access, which significantly enhances governance and reduces infrastructure overhead. According to Dremio, January 2025, in the 'State of the Data Lakehouse in the AI Era' report, 67% of organizations plan to run the majority of their analytics on data lakehouses within the next three years, underscoring the rapid industrial pivot toward this consolidated framework.

Integration of Generative AI for Augmented Data Engineering is emerging as a critical trend to address the widening skills gap and the increasing complexity of data pipelines. By embedding large language models directly into development workflows, engineering teams are automating labor-intensive tasks such as code generation, schema mapping, and legacy system documentation. This shift moves the focus from manual coding to architectural oversight, significantly accelerating the delivery of reliable data products while minimizing technical debt associated with human error. According to Ascend.io, September 2025, in the 'Annual Pulse Survey', 83% of data engineers stated that AI and new tools have increased their productivity, highlighting the transformative impact of intelligent automation on the services lifecycle.

Segmental Insights

Market research identifies Small & Medium-Sized Enterprises as the fastest-growing segment in the Global Big Data and Data Engineering Services Market. This rapid development is primarily driven by the increasing accessibility of cloud-based platforms, which eliminate the need for heavy upfront infrastructure investments. Consequently, smaller organizations are adopting data engineering solutions to enhance operational agility and enable data-driven decision-making essential for competitive survival. Furthermore, the availability of scalable, consumption-based service models allows these enterprises to efficiently manage expanding data volumes, thereby democratizing access to advanced analytics capabilities previously reserved for larger corporations.

Regional Insights

North America dominates the Global Big Data and Data Engineering Services Market primarily due to the extensive presence of major technology corporations and substantial investment in research. The region demonstrates early adoption of analytical tools across established industries, including finance and healthcare. Furthermore, stringent data privacy requirements enforce the implementation of secure data infrastructures. This strong focus on governance drives consistent demand for engineering services to ensure compliance. Consequently, the United States remains the primary contributor to regional expansion by deploying scalable data solutions to support business intelligence.

Recent Developments

  • In June 2024, Databricks Inc. introduced a new solution called LakeFlow, a native tool designed to simplify the construction and management of data pipelines for data engineering teams. Unveiled at the Data + AI Summit, LakeFlow offers a unified experience for data ingestion, transformation, and orchestration, integrating capabilities from the company's previous acquisition of Arcion. The tool enables users to ingest data from various databases and enterprise applications directly into the Data Intelligence Platform with scalable, low-latency processing. This launch addresses the increasing complexity of data engineering workflows, aiming to provide a more efficient and governed approach to preparing data for analytics and artificial intelligence applications.
  • In May 2024, Accenture agreed to acquire Parsionate, a data consultancy firm specializing in data products and modern data foundation services. This acquisition was intended to significantly bolster the company's data and artificial intelligence capabilities across Europe, particularly within the retail, industrial, and life sciences sectors. Parsionate brings extensive expertise in data strategy, data engineering, and master data management, adding a specialized team of consultants and architects to the technology group. The collaboration focuses on helping clients establish the robust digital cores necessary for harnessing generative AI, emphasizing the critical role of data readiness and engineering architectures in achieving successful business outcomes.
  • In February 2024, International Business Machines Corporation (IBM) announced a definitive agreement to acquire the application integration and enterprise technology platforms of Software AG for approximately €2.13 billion. This strategic acquisition focused on incorporating StreamSets and webMethods into IBM’s portfolio to strengthen its data fabric and artificial intelligence offerings. StreamSets provides modern data ingestion capabilities that are critical for training AI models, while webMethods facilitates the integration of applications and APIs across hybrid multi-cloud environments. This move was aimed at enhancing the data engineering infrastructure available to clients, ensuring they can effectively manage and leverage disparate data sources for advanced analytics and AI-driven business transformation.
  • In February 2024, Wipro Limited launched the Enterprise Artificial Intelligence (AI)-Ready Platform, a new service suite designed to help clients create fully integrated and customized AI environments. Developed in an expanded partnership with IBM, this platform leverages the watsonx AI and data capabilities, including watsonx.data and watsonx.governance, to accelerate the adoption of generative AI. The service offers a comprehensive set of capabilities spanning tools, large language models, and robust governance frameworks essential for modern data engineering. This initiative positions the company to better address the growing demand for reliable data foundations required to support complex, enterprise-scale artificial intelligence workloads and digital transformation projects.

Key Market Players

  • Accenture PLC
  • Genpact Inc.
  • Cognizant Technology Solutions Corporation
  • Infosys Limited
  • Capgemini SE
  • NTT Data Inc.
  • Mphasis Limited
  • L&T Technology Services
  • Hexaware Technologies Inc.
  • KPMG LLP

By Organization Size

By Business Function

By End User

By Region

  • Small & Medium-Sized Enterprises
  • Large Enterprises
  • Finance
  • Marketing & Sales
  • HR
  • Others
  • Media & Telecom
  • BFSI
  • Manufacturing
  • Government
  • Others
  • North America
  • Europe
  • Asia Pacific
  • South America
  • Middle East & Africa

Report Scope:

In this report, the Global Big Data and Data Engineering Services Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

  • Big Data and Data Engineering Services Market, By Organization Size:
  • Small & Medium-Sized Enterprises
  • Large Enterprises
  • Big Data and Data Engineering Services Market, By Business Function:
  • Finance
  • Marketing & Sales
  • HR
  • Others
  • Big Data and Data Engineering Services Market, By End User:
  • Media & Telecom
  • BFSI
  • Manufacturing
  • Government
  • Others
  • Big Data and Data Engineering Services Market, By Region:
  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • France
    • United Kingdom
    • Italy
    • Germany
    • Spain
  • Asia Pacific
    • China
    • India
    • Japan
    • Australia
    • South Korea
  • South America
    • Brazil
    • Argentina
    • Colombia
  • Middle East & Africa
    • South Africa
    • Saudi Arabia
    • UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Big Data and Data Engineering Services Market.

Available Customizations:

Global Big Data and Data Engineering Services Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Global Big Data and Data Engineering Services Market is an upcoming report to be released soon. If you wish an early delivery of this report or want to confirm the date of release, please contact us at [email protected]

Table of content

Table of content

1.    Product Overview

1.1.  Market Definition

1.2.  Scope of the Market

1.2.1.  Markets Covered

1.2.2.  Years Considered for Study

1.2.3.  Key Market Segmentations

2.    Research Methodology

2.1.  Objective of the Study

2.2.  Baseline Methodology

2.3.  Key Industry Partners

2.4.  Major Association and Secondary Sources

2.5.  Forecasting Methodology

2.6.  Data Triangulation & Validation

2.7.  Assumptions and Limitations

3.    Executive Summary

3.1.  Overview of the Market

3.2.  Overview of Key Market Segmentations

3.3.  Overview of Key Market Players

3.4.  Overview of Key Regions/Countries

3.5.  Overview of Market Drivers, Challenges, Trends

4.    Voice of Customer

5.    Global Big Data and Data Engineering Services Market Outlook

5.1.  Market Size & Forecast

5.1.1.  By Value

5.2.  Market Share & Forecast

5.2.1.  By Organization Size (Small & Medium-Sized Enterprises, Large Enterprises)

5.2.2.  By Business Function (Finance, Marketing & Sales, HR, Others)

5.2.3.  By End User (Media & Telecom, BFSI, Manufacturing, Government, Others)

5.2.4.  By Region

5.2.5.  By Company (2025)

5.3.  Market Map

6.    North America Big Data and Data Engineering Services Market Outlook

6.1.  Market Size & Forecast

6.1.1.  By Value

6.2.  Market Share & Forecast

6.2.1.  By Organization Size

6.2.2.  By Business Function

6.2.3.  By End User

6.2.4.  By Country

6.3.    North America: Country Analysis

6.3.1.    United States Big Data and Data Engineering Services Market Outlook

6.3.1.1.  Market Size & Forecast

6.3.1.1.1.  By Value

6.3.1.2.  Market Share & Forecast

6.3.1.2.1.  By Organization Size

6.3.1.2.2.  By Business Function

6.3.1.2.3.  By End User

6.3.2.    Canada Big Data and Data Engineering Services Market Outlook

6.3.2.1.  Market Size & Forecast

6.3.2.1.1.  By Value

6.3.2.2.  Market Share & Forecast

6.3.2.2.1.  By Organization Size

6.3.2.2.2.  By Business Function

6.3.2.2.3.  By End User

6.3.3.    Mexico Big Data and Data Engineering Services Market Outlook

6.3.3.1.  Market Size & Forecast

6.3.3.1.1.  By Value

6.3.3.2.  Market Share & Forecast

6.3.3.2.1.  By Organization Size

6.3.3.2.2.  By Business Function

6.3.3.2.3.  By End User

7.    Europe Big Data and Data Engineering Services Market Outlook

7.1.  Market Size & Forecast

7.1.1.  By Value

7.2.  Market Share & Forecast

7.2.1.  By Organization Size

7.2.2.  By Business Function

7.2.3.  By End User

7.2.4.  By Country

7.3.    Europe: Country Analysis

7.3.1.    Germany Big Data and Data Engineering Services Market Outlook

7.3.1.1.  Market Size & Forecast

7.3.1.1.1.  By Value

7.3.1.2.  Market Share & Forecast

7.3.1.2.1.  By Organization Size

7.3.1.2.2.  By Business Function

7.3.1.2.3.  By End User

7.3.2.    France Big Data and Data Engineering Services Market Outlook

7.3.2.1.  Market Size & Forecast

7.3.2.1.1.  By Value

7.3.2.2.  Market Share & Forecast

7.3.2.2.1.  By Organization Size

7.3.2.2.2.  By Business Function

7.3.2.2.3.  By End User

7.3.3.    United Kingdom Big Data and Data Engineering Services Market Outlook

7.3.3.1.  Market Size & Forecast

7.3.3.1.1.  By Value

7.3.3.2.  Market Share & Forecast

7.3.3.2.1.  By Organization Size

7.3.3.2.2.  By Business Function

7.3.3.2.3.  By End User

7.3.4.    Italy Big Data and Data Engineering Services Market Outlook

7.3.4.1.  Market Size & Forecast

7.3.4.1.1.  By Value

7.3.4.2.  Market Share & Forecast

7.3.4.2.1.  By Organization Size

7.3.4.2.2.  By Business Function

7.3.4.2.3.  By End User

7.3.5.    Spain Big Data and Data Engineering Services Market Outlook

7.3.5.1.  Market Size & Forecast

7.3.5.1.1.  By Value

7.3.5.2.  Market Share & Forecast

7.3.5.2.1.  By Organization Size

7.3.5.2.2.  By Business Function

7.3.5.2.3.  By End User

8.    Asia Pacific Big Data and Data Engineering Services Market Outlook

8.1.  Market Size & Forecast

8.1.1.  By Value

8.2.  Market Share & Forecast

8.2.1.  By Organization Size

8.2.2.  By Business Function

8.2.3.  By End User

8.2.4.  By Country

8.3.    Asia Pacific: Country Analysis

8.3.1.    China Big Data and Data Engineering Services Market Outlook

8.3.1.1.  Market Size & Forecast

8.3.1.1.1.  By Value

8.3.1.2.  Market Share & Forecast

8.3.1.2.1.  By Organization Size

8.3.1.2.2.  By Business Function

8.3.1.2.3.  By End User

8.3.2.    India Big Data and Data Engineering Services Market Outlook

8.3.2.1.  Market Size & Forecast

8.3.2.1.1.  By Value

8.3.2.2.  Market Share & Forecast

8.3.2.2.1.  By Organization Size

8.3.2.2.2.  By Business Function

8.3.2.2.3.  By End User

8.3.3.    Japan Big Data and Data Engineering Services Market Outlook

8.3.3.1.  Market Size & Forecast

8.3.3.1.1.  By Value

8.3.3.2.  Market Share & Forecast

8.3.3.2.1.  By Organization Size

8.3.3.2.2.  By Business Function

8.3.3.2.3.  By End User

8.3.4.    South Korea Big Data and Data Engineering Services Market Outlook

8.3.4.1.  Market Size & Forecast

8.3.4.1.1.  By Value

8.3.4.2.  Market Share & Forecast

8.3.4.2.1.  By Organization Size

8.3.4.2.2.  By Business Function

8.3.4.2.3.  By End User

8.3.5.    Australia Big Data and Data Engineering Services Market Outlook

8.3.5.1.  Market Size & Forecast

8.3.5.1.1.  By Value

8.3.5.2.  Market Share & Forecast

8.3.5.2.1.  By Organization Size

8.3.5.2.2.  By Business Function

8.3.5.2.3.  By End User

9.    Middle East & Africa Big Data and Data Engineering Services Market Outlook

9.1.  Market Size & Forecast

9.1.1.  By Value

9.2.  Market Share & Forecast

9.2.1.  By Organization Size

9.2.2.  By Business Function

9.2.3.  By End User

9.2.4.  By Country

9.3.    Middle East & Africa: Country Analysis

9.3.1.    Saudi Arabia Big Data and Data Engineering Services Market Outlook

9.3.1.1.  Market Size & Forecast

9.3.1.1.1.  By Value

9.3.1.2.  Market Share & Forecast

9.3.1.2.1.  By Organization Size

9.3.1.2.2.  By Business Function

9.3.1.2.3.  By End User

9.3.2.    UAE Big Data and Data Engineering Services Market Outlook

9.3.2.1.  Market Size & Forecast

9.3.2.1.1.  By Value

9.3.2.2.  Market Share & Forecast

9.3.2.2.1.  By Organization Size

9.3.2.2.2.  By Business Function

9.3.2.2.3.  By End User

9.3.3.    South Africa Big Data and Data Engineering Services Market Outlook

9.3.3.1.  Market Size & Forecast

9.3.3.1.1.  By Value

9.3.3.2.  Market Share & Forecast

9.3.3.2.1.  By Organization Size

9.3.3.2.2.  By Business Function

9.3.3.2.3.  By End User

10.    South America Big Data and Data Engineering Services Market Outlook

10.1.  Market Size & Forecast

10.1.1.  By Value

10.2.  Market Share & Forecast

10.2.1.  By Organization Size

10.2.2.  By Business Function

10.2.3.  By End User

10.2.4.  By Country

10.3.    South America: Country Analysis

10.3.1.    Brazil Big Data and Data Engineering Services Market Outlook

10.3.1.1.  Market Size & Forecast

10.3.1.1.1.  By Value

10.3.1.2.  Market Share & Forecast

10.3.1.2.1.  By Organization Size

10.3.1.2.2.  By Business Function

10.3.1.2.3.  By End User

10.3.2.    Colombia Big Data and Data Engineering Services Market Outlook

10.3.2.1.  Market Size & Forecast

10.3.2.1.1.  By Value

10.3.2.2.  Market Share & Forecast

10.3.2.2.1.  By Organization Size

10.3.2.2.2.  By Business Function

10.3.2.2.3.  By End User

10.3.3.    Argentina Big Data and Data Engineering Services Market Outlook

10.3.3.1.  Market Size & Forecast

10.3.3.1.1.  By Value

10.3.3.2.  Market Share & Forecast

10.3.3.2.1.  By Organization Size

10.3.3.2.2.  By Business Function

10.3.3.2.3.  By End User

11.    Market Dynamics

11.1.  Drivers

11.2.  Challenges

12.    Market Trends & Developments

12.1.  Merger & Acquisition (If Any)

12.2.  Product Launches (If Any)

12.3.  Recent Developments

13.    Global Big Data and Data Engineering Services Market: SWOT Analysis

14.    Porter's Five Forces Analysis

14.1.  Competition in the Industry

14.2.  Potential of New Entrants

14.3.  Power of Suppliers

14.4.  Power of Customers

14.5.  Threat of Substitute Products

15.    Competitive Landscape

15.1.  Accenture PLC

15.1.1.  Business Overview

15.1.2.  Products & Services

15.1.3.  Recent Developments

15.1.4.  Key Personnel

15.1.5.  SWOT Analysis

15.2.  Genpact Inc.

15.3.  Cognizant Technology Solutions Corporation

15.4.  Infosys Limited

15.5.  Capgemini SE

15.6.  NTT Data Inc.

15.7.  Mphasis Limited

15.8.  L&T Technology Services

15.9.  Hexaware Technologies Inc.

15.10.  KPMG LLP

16.    Strategic Recommendations

17.    About Us & Disclaimer

Figures and Tables

Frequently asked questions

Frequently asked questions

The market size of the Global Big Data and Data Engineering Services Market was estimated to be USD 71.98 Billion in 2025.

North America is the dominating region in the Global Big Data and Data Engineering Services Market.

Small & Medium-Sized Enterprises segment is the fastest growing segment in the Global Big Data and Data Engineering Services Market.

The Global Big Data and Data Engineering Services Market is expected to grow at 11.34% between 2026 to 2031.

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