Enterprise-Grade Data Engineering for Regulated Environments
We provide end-to-end data engineering solutions for companies with zero tolerance for errors in their data infrastructure, the kind that insurance and finance industries run on every day. This gives your data real value, ready to power analytics and AI across your business.
Engineering Data Foundations for Enterprise-Scale Operations
From modernizing legacy data environments and connecting fragmented systems to creating AI-ready data platforms, these are some of the ways we've helped organizations unlock more value from their data with our data engineering consulting service.
Still Waiting Days for Reports That Should Take Seconds?
Our data engineering experts don't just speed up reporting; they build it to hold steady under volume and stand up to regulatory review. Tell us about your reporting challenges to get started.
Data Engineering Expertise for Complex Business Environments
Data pipelines are just the starting point. Our data engineering consulting service extends to building scalable data platforms that power reporting, analytics, automation, compliance, and AI initiatives from a single trusted source of data.
- Automated data workflows freeing teams from repetitive data preparation and manual reconciliation work.
- AI-ready data foundations that reduce the cost and complexity of launching AI initiatives.
- Legacy-to-cloud migrations creating a foundation better aligned with future business priorities.
- Data ecosystems that replace spreadsheets and manual reporting with a single view of business performance.
- High-volume data platforms supporting thousands of transactions without compromising performance or reliability.
Data Engineering Services for Connected, High-Quality Enterprise Data
We help enterprises reduce manual data management through automated data flows and create a reliable data foundation for business-critical applications.
Data Integration and Pipeline Engineering
- Build ETL and ELT pipelines that work automatically. Data collection, transformation, and delivery all happen without manual effort.
- Support both real-time streaming and scheduled data pipelines for timely business insights.
- Integrate business applications, databases, APIs, & cloud platforms into a single data environment.
- Check, clean, and standardize your data before it flows into your warehouse, lakehouse, or reporting system.
Data Warehouse & Lakehouse Solutions
- Build centralized data warehouses that give your enterprise analytics a trusted foundation.
- Develop lakehouse environments that support multiple data types and analytics requirements.
- Structure and model business data to improve reporting consistency and decision-making.
- Fine-tune warehouse performance and storage to deliver faster insights at lower operational costs.
Cloud Data Platform Engineering
- Build secure, scalable cloud data platforms on Azure, AWS, Snowflake, Microsoft Fabric, and Databricks.
- Modernize legacy data platforms to support the next generation of business capabilities.
- Build reliable data platforms that are ready for unexpected disruptions.
- Put access controls and data governance in place to protect your sensitive business data.
Data Analytics & Business Intelligence
- Deliver the right information to every user through role-based dashboards.
- Offer live data reporting that speeds up decisions, from daily operations to long-term planning.
- Design intuitive data visualizations that simplify complex business information.
- Enable self-service analytics so business users can find answers from data without relying on IT.
From Fragmented Systems to Data Every Team Can Query Trust, and Use.
Beyond Core Data Engineering Solutions
Specialized capabilities that extend our core solutions with the technical depth enterprise data environments demand.
Enterprise Data Governance
- Regulatory compliance support
- Enterprise-wide data visibility
- Clear data ownership
- Data policy management
- Consistent data standards
- Data lineage tracking
Data Quality Management
- Duplicate record removal
- Missing data validation
- Automated data cleansing
- Standardized data formats
- Real-time quality monitoring
- Data consistency checks
Data Migration
- Legacy data platform modernization
- Cloud data migration
- Data integrity validation and reconciliation
- High-volume data migration
- Zero-downtime migration planning
- Cross-platform data migration
Data Security & Compliance
- Sensitive data protection
- Data encryption
- Data masking
- Data loss prevention
- Audit trail management
- Role-based access control
Data Activation
- Business application integration
- Cross-platform data synchronization
- Operational workflow automation
- Real-time operational data delivery
- AI application enablement
- In-app analytics integration
Data Observability
- End-to-end pipeline monitoring
- Timely data availability
- Automated schema change detection
- Data anomaly identification
- Proactive issue alerts
- Faster root cause resolution
Data Lifecycle Management
- Data retention policies
- Data archival & retrieval
- Data lifecycle automation
- Long-term data preservation
- Storage cost optimization
- Secure data disposal
Data Sharing & Collaboration
- Secure internal data sharing
- External partner data exchange
- Governed data distribution
- API-based data sharing
- Collaborative data workspaces
- Self-service data access
Enterprise Data Governance
- Regulatory compliance support
- Enterprise-wide data visibility
- Clear data ownership
- Data policy management
- Consistent data standards
- Data lineage tracking
Data Quality Management
- Duplicate record removal
- Missing data validation
- Automated data cleansing
- Standardized data formats
- Real-time quality monitoring
- Data consistency checks
Data Migration
- Legacy data platform modernization
- Cloud data migration
- Data integrity validation and reconciliation
- High-volume data migration
- Zero-downtime migration planning
- Cross-platform data migration
Data Security & Compliance
- Sensitive data protection
- Data encryption
- Data masking
- Data loss prevention
- Audit trail management
- Role-based access control
Data Activation
- Business application integration
- Cross-platform data synchronization
- Operational workflow automation
- Real-time operational data delivery
- AI application enablement
- In-app analytics integration
Data Observability
- End-to-end pipeline monitoring
- Timely data availability
- Automated schema change detection
- Data anomaly identification
- Proactive issue alerts
- Faster root cause resolution
Data Lifecycle Management
- Data retention policies
- Data archival & retrieval
- Data lifecycle automation
- Long-term data preservation
- Storage cost optimization
- Secure data disposal
Data Sharing & Collaboration
- Secure internal data sharing
- External partner data exchange
- Governed data distribution
- API-based data sharing
- Collaborative data workspaces
- Self-service data access
Solutions Engineered for Industry-Specific Demands
We design data engineering solutions around how your industry works, its data volume, its regulations, and its reporting demands. Every solution is built with AI-readiness at its core.
Manufacturing
- Industrial IoT Data Platforms
- KPI & Reporting Platforms
- Predictive Maintenance Data Models
- Equipment & Asset Data Integration
- Multi-Plant Data Consolidation Platforms
Finance
- Real-Time Financial Dashboards
- Risk Analytics Data Foundations
- Regulatory Reporting Ecosystems
- Customer Financial Intelligence Platforms
- Fraud Detection Data Foundations
Retail and eCommerce
- Customer 360 Data Platforms
- Point of Sale (POS) Data Integration
- Product & Catalog Data Management
- Omnichannel Data Integration
- Demand Forecasting Data Solutions
Insurance
- Claims Analytics Platforms
- Underwriting Intelligence Platforms
- Policy Data Integration
- Fraud Detection Platforms
- Policyholder Analytics
Healthcare
- Electronic Health Record Integration
- Clinical Research Data Platforms
- Patient Journey Analytics
- Pharmacy Data Integration
- Claims & Billing Data Integration
Supply Chain and Logistics
- Demand & Supply Planning Solutions
- Fleet & Transportation Data Integration
- Warehouse Data Platforms
- Inventory Analytics Platforms
- Order Fulfillment Analytics
SaaS & Technology
- Streaming Data Pipelines
- AI Training Data Pipelines
- Subscription & Revenue Analytics
- Application Performance Analytics
- User Behavior Analytics
Telecommunications
- Network Performance Analytics
- Usage & Billing Analytics
- Subscriber Data Integration
- Service Assurance Analytics
- Network Capacity Planning
Technology That Fits Your Data Strategy
Our data engineering consultants work with technologies behind today’s leading data platforms, building data foundations that can scale and support future innovation.
Cloud Data Platforms
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Microsoft Fabric
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Snowflake
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Azure Synapse Analytics
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Amazon Redshift
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BigQuery
Data Integration & Storage
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Azure Data Factory
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Azure Logic Apps
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Azure Data Lake Storage Gen2
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Azure SQL Database
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Delta Lake
Data Processing & Transformation
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Azure Databricks
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Apache Spark
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PySpark
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Python
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dbt
Streaming & Real-Time Data
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Azure Event Hubs
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Azure Stream Analytics
Analytics & Business Intelligence
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Power BI
Before AI Comes Better Data
The biggest challenge in AI is the quality of the data behind it. We help you get that right.
A Proven History of Data Engineering Excellence
Behind each case study is a data problem that was actively costing the business time, accuracy, or trust, until we solved it.
Client Testimonials
Our products last, and so do our relationships — we’re in it with you for the long run.
"We're impressed with their strong understanding of our business needs." Arna Softech has delivered a functional solution that aligns with the defined user stories, meeting expectations. The team works in sprints and manages their tasks effectively. Their strong understanding of the client's business needs allows them to tailor innovative solutions to match.
Yusuf Kilic
Co-founder - Consulting Company
"They seemed to hold themselves to higher, European quality standards." Thanks to Arna Softech’s work, the client improved their profile in the market. The team successfully delivered functioning products on time and within budget. Moreover, they communicated effectively and were responsive, flexible, efficient, and well-organized throughout the engagement.
Susana Araujo
CFO, a-connect
"Their work meets our acceptance criteria." The client was satisfied with Arna Softech's work and performance. The team has successfully delivered the first version of the proof of concept, and they're timely, efficient, and communicative. through emails and messaging apps. Overall, they offer a great service; there's nothing to improve.
Trevor Handley
Software Director, Rooster Asset Tracking
Questions We Hear Often
What Data Engineering Solutions Do We Need for Reliable, Real‑Time Reporting in Our Business?
Reliable, real-time reporting requires:
- Automated data pipelines to collect and move data from business applications.
- Connect data across business systems to create a complete view of your operations.
- Data transformation to clean and prepare data for analysis.
- A data warehouse or lakehouse that keeps reporting data organized.
- BI dashboards to visualize KPIs and operational metrics in real time.
- Data quality monitoring to ensure reports remain accurate & consistent.
How Can a Data Engineering Service Provider Help Us Choose Between Snowflake, BigQuery or Databricks?
A data engineering consulting company looks closely at your data volumes, analytics needs, AI goals, cloud environment, and budget. It then suggests a platform that best fits your business.
How Should I Evaluate a Data Engineering Service Provider for My Industry Use Cases?
Good data engineering partners get curious about your business. Here’s what to check:
- Relevant experience with businesses like yours.
- Expertise across your preferred cloud and data technologies.
- A proven approach to data quality, governance, and security.
- A portfolio demonstrating measurable business impact.
- The capability to scale with your future reporting and analytics.
What Data Engineering is Needed to Safely Use AI Tools Like ChatGPT on Our Internal Business Data?
To safely use AI tools with internal business data, you need secure data pipelines, centralized & trusted data storage, role-based access controls, data classification, and sensitive data masking where required. This allows AI to access only authorized data.
When Can We Expect to See Business Value from a Data Engineering Implementation?
Most businesses start seeing value in just a few months. Thanks to improved reporting, faster data access, and reduced manual work. Starting with high-impact use cases helps deliver value faster.