Data-driven insights for better business decisions
Fragmented data platforms, limited in-house expertise, and data quality concerns can hinder businesses from making the timely and data-driven decisions required to stay competitive. Our end-to-end data engineering services eliminate these challenges by improving how you manage your data at every stage of the data lifecycle.
From data collection and transformation to AI-enhanced analytics, our scalable solutions turn your raw data into business results. As your data engineering service provider, Intellias will cut your time to insights, improve your data accuracy, and increase user adoption across your company.
Challenges we solve with data analytics engineering services
Drive informed decisions
Base business choices on empirical evidence.
Maximize data ROI
Extract more insights and value from existing data.
Break down data silos
Enable data flows between departments for a holistic view.
Minimize business risks
Implement governance processes to mitigate potential issues.
Strengthen your market position
Use quality data for product development and customer retention.
We provide end-to-end data engineering services
ETL / ELT / integration
We extract and transform historical data from diverse sources including REST APIs, FTP, databases, and legacy systems with proprietary protocols.
- ETL/ELT development
- Batch & real-time stream processing
- Scalable data pipelines
- Data integration solutions
Data warehouse
Our data architects design and manage robust ecosystems that centralize and organize structured quality data, enabling complex querying, reporting, and analytics.
- Data modeling & schema design
- Metadata management
- Data source integration
- Data process automation
- DWH migration & optimization
- Analytics & reporting
Data lake & data lakehouse
Data lake solutions we provide will help you store, safeguard, and analyze vast datasets and data types from various sources across your enterprise.
- Data lake design & implementation
- Data ingestion & integration
- Data governance & security
- Data catalog & metadata management
- Advanced analytics & machine learning
Data fabric
With our data integration engineering services, we create a unified virtual data layer for centralized data management, governance, and self-service access across distributed environments.
- Augmented data catalog
- Knowledge graph
- Metadata activation
- DataOps
Data mesh
We implement data mesh architectures that empower your domain experts by distributing data ownership within a scalable framework.
- Data ingestion
- Data transformation
- Data preparation
- Federated learning
Big data solutions
With our big data engineering services, we build cloud-native, cloud-agnostic, and on-premises platforms for smoothly handling your large-scale data processing needs.
- Data ingestion & storage
- Data processing & cleaning
- Data integration & transformation
- Big data analytics & visualization
- Data pipeline orchestration
Our approach focuses on continuous improvement
Our end-to-end data engineering consulting services allow you to build resilient pipelines for high-quality data delivery through our D.R.E.A.M Framework:
D
Discovery and assessment
Evaluate your data landscape to identify opportunities, assess infrastructure readiness, and streamline data processes.
R
Roadmap design
Create a data strategy that prioritizes conformity, governance, and privacy; AI/ML integration; and low-code technologies for an efficient data flow, from ingestion to analysis.
E
Execution and implementation
Set up data infrastructure, platforms, and pipelines, deploying real-time observability tools for effective data workload management and self-service access.
A
Adjustment and improvement
Feedback and performance metrics analyzed to adjust strategy and implementation to optimize performance.
M
Maintenance and support
Address governance, literacy, cataloging, lineage tracking, and quality management with ongoing updates and support.
Brands around the world trust us
Clients appreciate us
Specifically, Intellias has helped us to optimize and evolve Data Hub architecture atop Azure cloud. The Data Hub architecture includes the Landing Zone and the mechanisms for data ingestion, processing, and curation to enable users to receive information from different data sources simultaneously. Intellias and our company paid a lot of attention to data security and compliance, so the data was anonymized for storage in the cloud. Additionally, Intellias has piloted the concept of training AI/ML algorithms to help our business analyze user behavior, predict future client payments, and make more informed business decisions.
The Intellias team has played a crucial role in automating and enhancing the process of data collection and analysis, leading to a significant reduction in decision-making time from several days to a few minutes. By leveraging strong automation capabilities and seamless integrations, Intellias engineers have made significant contributions to the creation of a user-friendly, highly stable, and secure product.
Intellias has a culture that renders results; their people are motivated, and I believe this is their key strength.
Our partners are leading technology providers
We combine our data engineering consultancy with strong tech partnerships, offering you flexible access to the best-fitting solutions without lock-in.
Ecosystem partnerships
Why clients turn to Intellias for their data engineering needs
Industry-specific solutions
We understand the unique data challenges in your field. Our data engineering consultants help you create data solutions that add value and meet your industry requirements.
Faster insights
Say goodbye to data chaos! Our technical advisory and digital solutions help you generate insights quickly, enabling smarter decisions across your organization.
Smart automation
Save money and minimize errors by automating data flows. This frees your teams from manual tasks, allowing them to be more productive with key activities.
Future-ready architecture
Build a strong data ecosystem that scales with your business. Our resilient high-end solutions tackle current challenges and prevent expensive updates down the line.
3k+
experts
24
years of digital consulting and engineering
17
delivery locations
100+
completed data projects
Our data experts
Eugene Berko
Director of Technology Practices
Director of Technology Practices at Intellias with 13+ years of experience in software engineering, management, and consulting. The area of Yevhen’s responsibility is the company’s technology offering in the fields of Data & AI, Cybersecurity, IoT, Cloud & DevOps, Support, Intelligent Automation, Business Applications.
Driven by passion for learning and making a difference, Yevhen is also a firm believer in flexibility and providing a unique solution to each problem rather than following 300+ page frameworks. He often speaks publicly and is interested in the topic of using Generative AI to solve real-world business problems as well as the art and science of governing AI.
Viktor Sokolov
Head of Data Governance Unit
Viktor brings 20 years of expertise in data and analytics, with a strong focus on the finance, retail, and wireless communications sectors. His key areas of specialization include data governance, data warehouse development, data modeling, and the implementation of BI systems for large-scale data environments.
As the Head of the Data Governance Unit at Intellias, Viktor works with clients to implement strategic frameworks that ensure regulatory compliance, uphold data integrity, and maintain high standards of data quality.
FAQ
Our data engineering services ensure your business decisions are based on accurate, high-quality data. We help you collect, integrate, and process data to generate insights faster. With AI-enhanced analytics and automated workflows, we reduce manual efforts, allowing your teams to focus on strategic actions. The result? Timely, data-driven decisions that boost efficiency, minimize risks, and unlock new business opportunities.
We specialize in integrating data from various sources, including databases, REST APIs, FTP servers, and legacy systems with proprietary protocols. Our ETL and ELT solutions ensure seamless data extraction, transformation, and loading while maintaining data integrity.
Data security and compliance are at the core of our approach. We implement robust data governance frameworks, ensuring compliance with industry regulations such as GDPR, HIPAA, and SOC 2. Our solutions include encryption, anonymization, and access control mechanisms to protect sensitive data. Additionally, we integrate real-time observability tools for monitoring and securing data pipelines throughout their lifecycle.
Yes, we design cloud-native, cloud-agnostic, and hybrid data solutions that seamlessly integrate with leading cloud providers, including AWS, Azure, and Google Cloud. Our expertise in data platforms like Snowflake, Databricks, and BigQuery ensures optimal performance, scalability, and cost efficiency, helping you leverage the full potential of cloud-based analytics and storage.
We offer continuous support to keep your data infrastructure running smoothly. Our maintenance services include governance, data quality management, cataloging, and lineage tracking. We also provide updates, performance optimizations, and enhancements to align with your evolving business needs. With our proactive approach, we ensure your data solutions remain scalable, secure, and future-proof.
Opportunity to discuss data marketplaces, where an organization’s producers and consumers of data can make available, govern, consume, and price data and data products/artifacts.
Describe how Intellias makes the most current data available enterprise-wide, avoiding stale data sources.
Data is now considered an organizational asset that can be monetized by selling it. This might be to upstream suppliers or downstream channel partners, for example.
By cross-pollinating data sources with upstream and downstream partners, greater insights and optimization plays can be achieved versus constraining a solution to a given organization. This is beyond just integrating 3rd party data sources as it requires collaborative participation, sharing and actioning by all partners/parties involved.