Top 10 Data Engineering Companies in 2025

Data is the foundation of success in this digital world. In this cloud environment, the need for scalable and organized engineering is crucial. Data engineering makes this possible by establishing streamlined, reliable, and automated data pipelines. 

Data engineering companies provide the technical expertise to build these scalable data foundations and automate real-time processing. Data engineering companies help in enhancing efficiency and data quality. Through data pipeline automation, enterprises can reduce manual effort, minimize errors, and achieve measurable benefits.

This post will spotlight the top 10 Data Engineering consulting companies that have helped organizations ensure scalability and compliance.

What is Data engineering?

Data engineering means designing, building, and managing systems. These systems collect, store, and process raw data. The goal is to turn this data into usable formats for analysis and better decision-making.

It ensures data is reliable, available, and accurate. It forms the foundation of data science and business intelligence in an organization. Aspects of data engineering encompass data collection and ingestion, data storage, data processing, and data governance and quality assurance.

The key benefits of data engineering are: 

• It drives business value decisions
• Makes data usable
• Ensures data quality and Integrity
• They help us to build scalable data architectures.

How We Selected the Top Data Engineering Companies

It becomes essential for organizations to evaluate the data engineering companies based on measurable and clear criteria. Based on the factors below, we have selected the top data engineering companies.

• Years of experience: We have prioritized data engineering companies which hold long experience in handling complex enterprise projects.  We examined their market experience, which demonstrated their capability to deliver large-scale projects. Those companies that have this criterion will have emerging leaders in the data engineering space.
• Range of services offered: Top data engineering companies provide end-to-end services from ingestion and transformation to governance and analytics enablement. We have analyzed the data engineering companies' capabilities to provide common services like data pipeline development, data architectural design, cloud data migration, data governance and quality, database optimization, and management.
• Technology expertise: We have compiled the data engineering companies that have proven expertise in essential technologies for building scalable platforms and big data tools. Look for data engineering companies with deep expertise in data management, architecture, and analytics. Analyze their previous works and whether they can solve complex data challenges. Data engineering companies should deliver measurable results in your specific industry.
• Scalability: More preference is given to data engineering companies that offer scalable solutions. It should adapt to the needs of both startups and big organizations.
• Client feedback: We have gathered the customer feedback and independent client reviews from reputable platforms like Clutch. Any awards, certifications, and inclusion of reports are given more weight. 
• Pricing transparency: We have ranked the data engineering companies based on cost structures. It should be transparent and should not include any hidden charges. Pricing details are mentioned as available on the company websites or the Clutch platform.

Top Data Engineering Companies

1. Entrans

Entrans is a data engineering consulting and engineering company that offers digital transformation with AI-driven insights. We provide full-cycle data engineering and analytics services that turn raw data into actionable business insights.

Key Data Engineering Services of Entrans:

• AI and ML-Driven Business Insight: Entrans harnesses AI and ML for advanced analytics that reveal actionable insights. We turn your data into strategic assets that drive growth and innovation.
• Data modernization: As a prominent service provider, we help in migrating business data from legacy data systems to cloud systems. We also assist with migration, modernization, and management of databases. 
• Data pipelines: We design and implement data pipelines that collect, process, and move data across systems. We use tools and platforms like Azure, Databricks, Power BI, Tableau, and big data technologies. Our cloud experts help in data ingestion to extract and refine data from sources like databases, APIs, and streaming services, and consolidate it into centralized systems. Through ETL, we transform raw data into clean data ready for analysis and reporting. We also follow CI/CD pipelines to automate testing and deployment of data ingestion, staging, and transformation.
• Data warehouse and Data lake implementation: Whether it’s distributed computing or large-scale data ingestion, our engineers optimize your big data processing. Certified in Hadoop, Apache Spark, AWS S3, and Azure Storage accounts, we design scalable architectures for easy data management. Build a future-proof data lake with flexible configurations using cloud-native solutions on AWS, Azure, or Google Cloud.
• Data Security and Governance: Security is a top priority. Our experts ensure your data remains secure and compliant. We are certified in GDPR, SOC 2, and ISO standards and design practical data governance frameworks. By end-to-end encryption and centralized governance solutions on AWS, Azure, and Google Cloud, we tend to improve data security.
• Zero downtime delivery model: At Entrans, we ensure zero downtime from data integration to analytics deployment, which guarantees seamless updates, allowing your organization to access insights without any interruptions.
• Data Strategy and consulting: We also offer consulting services by analyzing the company’s current data maturity and guiding it in selecting the technologies and tools.

2. Databricks

Databricks is a data engineering platform provider that offers a unified data and AI platform used for data engineering. Their core data engineering solution is branded as Lakeflow.

Key Data Engineering Services of Databricks:

• Databricks provides an end-to-end data lifecycle from ingesting raw data to transforming it. Lakeflow provides ingestion connectors and declarative pipelines for both batch and streaming data.
• They provide a unified governance layer for all data and AI assets. They provide role-based access control (RBAC), lineage, and audit logging.
• Databricks also provides data engineering services such as migration from legacy systems, setting up lakehouse infrastructure, and performance tuning.

3. Accenture

Accenture, as a data engineering service provider, provides end-to-end data engineering services that help organizations build modern, scalable, and secure data foundations. 

Key Data Engineering Services of Accenture:

• Accenture creates automated data pipelines. These pipelines help generate, collect, and process large data sets.
• Accenture helps clients migrate their data to the cloud and enable them to build data platforms.
• They ensure to follow necessary frameworks and controls and make sure data is secure, compliant, and well-managed across the organization.

4. Deloitte

Deloitte, as a data engineering service provider, provides comprehensive data engineering services as part of its AI and Data practice. Deloitte combines strategy, technology, and implementation expertise to ensure data is accurate, accessible, and actionable.

Key Data Engineering Services of Deloitte:

• Deloitte provides data platform modernization services on major cloud platforms such as AWS, Microsoft Azure, and Google Cloud. They also help the client to migrate their legacy data centers and data systems to a cloud environment. 
• Deloitte specializes in implementing solutions for streaming and batch processing to handle high-velocity data.
• They also design optimal data models and schemas and ensure data is efficiently stored, retrieved, and available for the applications.

5. Snowflake

Snowflake is a platform provider that uses a cloud-based data warehouse and a data cloud platform for storing data and engineering.

Key Data Engineering Services of Snowflake:

• Snowflake offers services like Snowpipe for continuous integration and real-time data ingestion. They also support Snowpark Connect and OpenFlow for connecting to various streaming sources like Apache Kafka, unifying batch and streaming pipelines.
• Snowflake provides dynamic tables for declarative and materialized views based on freshness targets. 
• They also provide powerful tools for transforming data into the cloud using Snowflake Data Cloud. 

6. Fivetran

Fivetran is a data movement platform provider that is focused on automating and simplifying data ingestion. They also offer professional services to help optimize and scale the data.

Key Data Engineering Services of FiveTran:

• Fivetran has over 700+ pre-built connectors to data sources like SaaS apps, databases, ERPs, and files, to automate the extraction of data and load it into a centralized cloud destination.
• Fivetran’s platform is designed for enterprise-grade reliability, offering fault-tolerant pipelines. They offer data encryption, robust security compliance, and features to manage metadata and access controls. 

7. Slalom

Slalom is a data engineering consulting firm that specializes in cloud data platforms, analytics, and engineering solutions. Their main approach is to create custom software, data, and cloud products with clients, which accelerates digital transformation.

Key Data Engineering Services of Slalom:

• Slalom designs cloud data architecture, data warehouses, and data lakes/lakehouses by choosing appropriate tools and frameworks. This includes building modern data platforms, creating real-time/streaming data solutions, and establishing effective data ingestion.
• They help in establishing trust and control over their data by developing robust data governance frameworks and data management practices.

8. Simform

Simform is a data engineering service provider that offers data engineering, cloud, and AI services as part of its digital engineering portfolio.

Key Data Engineering Services of Simform:

• Simform builds customized and real-time integration using robust ETL and ELT solutions. They get data from various sources and consolidate it into a central data warehouse.
• Simform mainly does migration services for legacy data systems to modern, scalable cloud-based platforms.
• Simform ensures data is cleaned, properly prepared, and feature-engineered for establishing an integration between AI and machine Learning workloads (MLOps).

9. ScienceSoft

Sciencesoft is an IT consulting and software development company that offers data engineering services. They are one of the prominent long-standing providers of data and analytics projects.

Key Data Engineering Services of Sciencesoft:

• Sciencesoft provides consulting, design, and implementation of robust Data warehouse (DWH) and Big Data solutions. 
• They also support data integration solutions, including designing ETL (Extract, Transform, Load) or ELT pipelines. 
• As a consulting firm, they also provide services that implement data governance frameworks and policies that guarantee quality, security, and compliance.

10. ThoughtWorks

ThoughtWorks is a data engineering service provider that provides data platform engineering, analytics, and software development services. They combine strategy, design, and engineering.

Key Data Engineering Services of ThoughtWorks:

• ThoughtWorks helps organizations by using AI to solve complex business problems, deploying robust pipelines, and embedding governance.
• ThoughtWorks also does migration services from legacy systems, modern data architectures, and reference architectures.
• ThoughtWorks builds scalable data pipelines to ingest, transform, and process data, often integrating with ML/AI workflows.

Main Services Offered by Data Engineering Companies

Data Engineering services form the main foundation for business intelligence, data science, and machine learning initiatives. The main services offered by Data Engineering companies are

• Data Pipeline development (ETL/ELT): This is the core service of data engineering companies. They design and implement data pipelines that help in collecting, processing, and moving data across various systems. They integrate data from different sources like databases, SaaS, IoT devices, and legacy systems into unified repositories for easier access and analysis. Data engineering services companies design and automate ways to transform data. They turn it into a usable format. This is done in two ways: either before loading it into the destination (Extract, Transform, and Load) or transforming the data after loading it into a data warehouse or data lake (Extract, Load, and Transform). 
• Data Infrastructure design: This step is to create a structure, like a data warehouse or data lakes, which is used for data collection, storage, and processing. Data engineering companies design and implement data warehouses that serve as centralized hubs for structured and semi-structured data for small datasets. These warehouses are optimized for analytics, performance, reliability, and reporting. Some of the data warehouses are Snowflake, Amazon Redshift, and Google BigQuery. When there is a need for storing a large amount of raw, unstructured, or semi-structured data, data lakes are essential. Data lakes allow flexible storage and the use of AI and ML models.
• Data Governance and Quality: Data engineering companies implement frameworks for data validation and governance. They detect and correct errors, inconsistencies, and missing values in the data pipelines. They will also establish roles, standards for data usage, access, and security to ensure compliance. This will ensure the accuracy, consistency, security of data, and compliance.
• Data strategy and Consulting: As a data engineering service provider, they also offer strategic guidance and support for advanced data initiatives. They assess the company’s data maturing and establish a roadmap for selecting the best-suited technologies and tools. They apply DevOps principles such as automation, monitoring, CI/CD for the data pipelines, and accelerate the development.
• Data migration and cloud transformation: Data engineering consulting firms help in moving data infrastructure and workloads to modern cloud platforms. Thereby, help in upgrading legacy infrastructure. This ensures scalability, flexibility, agility, and cost optimization.
• Data optimization and maintenance: A data engineering consulting company will primarily prepare and manage the data sets required for training and deploying the machine learning models. They ensure the quality of the data sets. They provide ongoing support, performance tuning, and troubleshooting for the entire data infrastructure and pipelines.

How to Choose the Right Data Engineering Company for Your Business

Selecting a data engineering service company is crucial for utilizing data that impacts long-term ability. Here is a checklist to find the right big data engineering companies

• Define your goals: First, clearly identify the need for data engineering for your organization. Whether it is building data pipelines, modernizing legacy systems, migrating to a cloud data warehouse, implementing advanced analytics, or providing real-time insights.
• Industry experience and Technical expertise: Focus on data engineering firms that excel in creating data pipelines (ETL/ELT), data warehousing, data lake architecture, cloud platforms, data governance, and quality management. Check whether the data engineering company uses modern tools and platforms with AI and ML insights. This will certify their ability to give more future-ready solutions. 
• Partnerships and Certifications: Prefer data engineering services companies that have partnerships with cloud and data platforms such as AWS and Microsoft. These certifications will highlight their ability to design and implement optimized data solutions.
• Customer trust and reputation: Collect and review case studies and verified reviews from platforms like Clutch, G2, or GoodFirms. Assess the customer satisfaction, delivery timelines, communication, and ongoing support. Customers’ reviews will give a clear picture of the company’s reliability and performance.
• Security and compliance: Ensure that the data engineering company adheres to strong security measures and industry regulations. Check for relevant industry certifications such as ISO 27001.
• Communication and transparency: A strong data engineering partner will provide clear updates, collaborate effectively with teams, and address issues promptly.

Future Trends in Data Engineering

Data engineering is rapidly evolving as organizations generate and process more data than ever before. The future of data engineering is reshaped by AI, real-time insights, and distributed architectures.

• Integration of AI and machine learning: AI is acting as a co-pilot for humans. It automates tasks like code generation, documentation, testing, and data quality checks. AI is increasing productivity. Generative AI will revolutionize data-driven decision-making through modernization and migration.
• Low-Code/No-Code Platforms: The Future will see more non-data-engineering business users building basic data products or self-serve analysis. This will free up the data engineers from more complicated architectural work.
• Governance: Increased regulatory pressure, such as the EU AI Act, will make robust data governance, privacy, and compliance features non-negotiable for automation tools.
• Data Lakehouse architecture: The Data warehouse and data lake will be merged into a unified data lakehouse model. This will make structured and unstructured data coexist. Analytics and machine learning workloads will be combined in one platform. 
• Real-time data insights: More real-time analytics will be used for fraud detection, personalized recommendations, and immediate operational responses.

Why Choose Entrans as Your Data Engineering Partner?

Data engineering companies act as a bridge between data and decision-making. Partnering with the right data engineering company, like Entrans, is important to stay ahead in this era. 

We provide end-to-end engineering solutions from data ingestion to transformation. Our cloud engineers are well-versed in modern architectures like data lakes, lakehouses, and real-time streaming pipelines. 

Entrans makes future-ready solutions by providing continuous support, performance optimization, and evolving data strategies.

Want to know more about how we do the engineering process securely and of high quality? Book a consultation call.

Frequently Asked Questions (FAQs):

1. What do data engineering companies do?

Data engineering companies design, build, and maintain data pipelines. They use either data warehouses or data lakes to collect and store data. They mainly focus on making data reliable, accessible, and usable. 

2. How is data engineering different from data science?

Data engineering focuses on infrastructure and data flow, whereas data science focuses on analysis to extract insights and build predictive models.

3. Can data engineering integrate with my existing systems?

Yes, data engineering solutions are designed to integrate seamlessly with your existing systems, like databases, API, and applications. 

4. What is the timeline to complete and the cost for the data engineering project?

A data engineering project may depend on project complexity, scale, and engagement model. Timelines may vary from weeks; it costs thousands, while a full, large-scale project can take months and cost more.

5. How do you handle a new data engineering project?

A typical data engineering project starts with assessment, planning, followed by data pipelines and storage. Finally, we build, test, and deploy the system by ensuring data quality and security from source to destination.