Data Engineering Services
Disconnected systems and manual prep slow decisions and waste resources. We build custom data pipelines and web platforms that unify every source, deliver governed, high-quality data, and power real-time analytics and AI. With 20+ years of expertise and 50+ complex projects delivered, we help small and mid-sized companies cut reporting cycles by up to 70% and scale faster.
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Why companies choose DATAFOREST
Battle‑tested: 100+ engineers; 18+ years in data engineering & applied AI for US/EU mid‑market.
Unique expertise: 39 delivered industry-specific solutions across finance, utilities, healthcare, retail, and SaaS—giving us proven patterns, benchmarks, and accelerators we can apply to your case for competitive advantage through data engineering.
Outcomes first: KPIs defined up‑front business benefits (revenue lift, churn drop, cost per action, SLA).
Fast validation: 2‑week PoC to prove signal before full rollout.
Future-proof data architecture: Cloud-native data solutions are also elastic and AI-ready.
Governance built-in: PII handling, lineage, compliance (GDPR, HIPAA, SOC2).
Data Engineering Metaverse
We design the data engineering pipeline to ingest user interaction, feature usage logs, and feedback surveys. This data is then cleaned, transformed, and aggregated to identify usage patterns. The same pipeline is extended for Gen AI training data preparation to collect vast amounts of relevant data. DATAFOREST develops analytical models and dashboards, using big data integration, data management, and processing for large-scale platforms and observability for AI systems.
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Unlock 40+ hours of weekly efficiency - validated in a 2-week PoC.
01
Break Down Data Silos
Connect all your scattered databases, applications, and files into one customer data platform implementation. Teams can access complete information without having to search across multiple systems or wait for IT requests, enabling customer experience personalization.
02
End Manual Reporting
Replace hours of copying, pasting, and Excel formatting with automated pipelines that refresh dashboards in real-time. Your reports update themselves while you focus on analyzing insights instead of gathering data.
03
Fix Data Quality Issues
Catch errors, duplicates, and inconsistencies before they reach your dashboards through automated validation rules. Teams trust the numbers because the system flags problems and fixes common issues automatically.
04
Reduce Cloud Infrastructure Costs
Intelligent resource scheduling and compression reduce your AWS, Azure, or GCP bills by running workloads when compute is most cost-effective. Eliminate redundant storage and optimize query performance with database optimization techniques to stop paying for wasted resources.
05
Meet Compliance Requirements
Track every piece of sensitive data from source to destination with automated lineage mapping and access logs. Auditors can see exactly who accessed what info and when, while PII/PHI gets proper protection with financial data processing compliance and healthcare data engineering security.
The Base of Enterprise Data Integration as A Service
We deliver end-to-end solutions from automated pipeline orchestration to enterprise-grade governance, enabling scalable analytics and AI initiatives.
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ETL/ELT Orchestration
scalable workflows using Airflow, DBT, Kafka, APIs with ETL process optimization.
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Modeling & Schema Design
optimized structures, data modeling best practices for analytics and AI.
Data Governance
PII/PHI handling, lineage, approvals, data versioning strategies, and audit trails.
Infrastructure & DevOps
CI/CD, containerized services, microservices, data architecture, and cloud cost optimization.
Performance Measurement
The Retail company struggled with controlling sales and monitoring employees' performance. We implemented a software solution that tracks sales, customer service, and employee performance in real-time. The system also provides recommendations for improvements, helping the company increase profits and improve customer service.
They easily understand industry-specific data and KPIs, and their efficiency as a team allows them to deliver results quickly.
They developed solutions that brought value to our business.
All Success Stories
Case Studies in Data Engineering—Powering Decision-Making
200+ Reports Centralized for UK Property Finance Leader
Enra Group, the UK’s leading provider of specialist property finance, relied on 200+ Excel reports distributed by email, creating bottlenecks in daily operations and outdated insights.
They implemented a custom reporting platform that:
- Consolidated 200+ scattered reports into a single governed platform
- Automated data collection from multiple sources (emails, files, manual inputs)
- Integrated access control to ensure secure, role-based report sharing
Results:
- Reports load in under 5 seconds
- 200+ reports centralized and simplified
- Manual daily operations reduced
2× Policy Sales Growth for U.S. Insurance Agency with Automated Sales Platform
A U.S. digital insurance agency was stuck with a 32% retention rate, slow lead intake, and disengaged sales teams.
They implemented a custom automation solution that:
- Automated lead intake from top carriers (QuoteStorm, EverQuote, QuoteWizard, etc.)
- Unified CRM, AMS, CPaaS, and quote providers into one synchronized system
- Centralized customer communications (SMS, email, WhatsApp) in a Live Chat hub with AI support (ChatGPT, DialogFlow)
Results:
- 2× increase in new policy sales
- Customer retention improved from 32% → 58%
- Sales funnel expanded 5× with only a 25% team growth
Streamlined Data Analytics for U.S. Marketing Agency with Automated Data Warehouse
A U.S. digital marketing agency needed to unify fragmented data across multiple platforms (Treez, Google Analytics, LeafLink, SproutCRM) to improve client insights and campaign decisions.
They implemented a custom data engineering solution that:
- Built a centralized data warehouse with daily automated updates
- Automated ETL pipelines to clean, transform, and unify multi-source data
- Connected APIs for real-time data extraction and integration into BI tools
Results:
- 1.5M+ records integrated into a single reporting system
- 4+ sources consolidated into one BI environment
- Daily refreshed dashboards delivering actionable insights
Data Engineering Results That Drive Business Value
Transform operations with data engineering solutions that deliver time savings, cost reductions, and performance improvements for the ROI of modern data architecture.
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Decrease Manual Work
Automate data and save 40+ hours weekly by automating reporting processes and data consolidation tasks.
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Reduce Infrastructure Costs
Achieve 25–35% lower cloud expenses through optimized data architecture and resource management.
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Accelerate Decision-Making
Deliver 2–3× faster analytics by creating unified sources that eliminate information silos for data-driven decision making.
Build Data Confidence
Establish a trusted metrics organization-wide with comprehensive lineage tracking, monitoring, and compliance controls.
Our Data Engineering Stack
Our solutions leverage best-in-class tools across the modern ecosystem to deliver scalable, secure pipelines. We select the right combination of cloud platforms, orchestration tools, and governance frameworks based on your specific requirements and existing infrastructure.
Cloud & Data:
Pipelines & Orchestration:
Real-Time Processing:
Visualization & BI:
Governance & Security:
Five Process Steps
Our data engineering service is a collaborative five-step journey.
Complimentary Strategy Session
Our first session assesses your integration consulting company's needs and whether we're the right data engineering services company to help you turn data into business benefits.
01
Dive into Your Landscape
We inventory your sources and destinations to build a blueprint powered by data integration consulting, data warehouse implementation, and cloud integration services.
02
Crafting Your Solution
Our engineers use custom data pipeline development. DevOps ensures resilience for any public workload with SaaS data pipeline architectures aligned to your growth.
03
Your Solution, Delivered
Open collaboration, feedback loops, and continuous updates are our core principles in data engineering as a service.
04
Your Success, Our Commitment
We maintain and optimize systems through managed data integration services and data engineering consulting.
05
Data Integration Solutions Related Articles
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FAQ to Begin Data Integration Consulting
What services do you offer for data engineering projects?
We offer data engineering consulting, building scalable pipelines, and delivering cloud integration services and database integration services tailored to your business objectives. We also specialize in data integration solutions, uniting disparate systems and APIs for data engineering and performance optimization to ensure your data infrastructure is cost-effective and high-performing. DATAFOREST is among the seasoned data engineering service providers, managing services for the ongoing maintenance and support of the data environment.
How much time do data engineering companies take to complete a project?
Projects involving data engineering consulting services or customer data integration solutions vary by scope and tools used. Smaller projects focused on specific tasks like ETL pipeline development might take weeks and cost a few thousand dollars. In contrast, larger, more comprehensive projects involving analytics engineering services or custom solution development can span several months and cost tens or hundreds of thousands of dollars. It's crucial to get detailed info when calling our data engineering consultant.
Do you provide ongoing support and maintenance for data engineering solutions?
Our data integration and engineering services company delivers managed services and maintains modern architecture engineering services. This includes monitoring the health and performance of pipelines, cloud warehouse engineering services, and data science engineering services, applying updates and patches, and ensuring the system remains scalable and adaptable to evolving business needs. These modern architecture engineering services are crucial for maintaining the long-term value of data engineering investments.
What is the cost structure for your data engineering services?
We charge based on design, implementation, and data integration automation, with variable ongoing costs for support and updates, as well as potentially usage-based fees based on data volume or processing time. The specific cost structure will vary significantly depending on the project's complexity and the level of customization required to address clients' problems.
Can you assist with cloud migration and data integration in data engineering?
We use data engineering software and specialize in cloud data integration solutions, ETL, and engineering outsourcing. We help businesses seamlessly migrate their infrastructure and workloads to cloud platforms, ensuring minimal disruption and maximum efficiency. We also integrate disparate systems, applications, and sources to establish a unified view of a company's information assets. The ETL migration engineering services ensure smooth data flows, accessibility, and usability for expert engineering solutions.
How do you collaborate with other teams, such as data scientists and business analysts, in data engineering projects?
DATAFOREST enables cognitive collaboration by aligning business objectives with automated data integration services and reliable data engineering automation. We also work closely with business analysts to understand their requirements, translate business goals into technical engineering solutions, and ensure that the data engineering projects deliver actionable insights aligned with the company's objectives. This cross-functional collaboration ensures a holistic approach to projects, bridging the gap between technical implementation and business value.
What platforms use your data engineering experts?
We leverage AWS, Azure, GCP, and tools such as Airflow and dbt across all our big data integration services. We also leverage open-source platforms like Apache Hadoop and Apache Spark for distributed processing and analysis. Additionally, for data engineering, analytics, and solutions, we use specialized tools like dbt for transformation and Airflow for workflow orchestration to streamline and automate pipelines.
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