Data Engineering Services

Build scalable, high-performance data pipelines that power your analytics and AI initiatives. Transform raw data into actionable insights with enterprise-grade data engineering solutions.

OVERVIEW

Enterprise Data Engineering Solutions

VarniViews delivers comprehensive data engineering services that enable organizations to build robust, scalable data infrastructure. Our expertise spans real-time streaming, batch processing, data lake architecture, and cloud-native data platforms.

60% Faster Processing

Reduce data processing time by up to 60% with optimized pipelines and efficient architecture design.

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Petabyte-Scale Data

Handle massive data volumes across multiple sources with enterprise-grade data platforms.

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Sub-Second Latency

Real-time insights with sub-second latency for time-sensitive business decisions.

OUR SERVICES

Comprehensive Data Engineering Capabilities

Data Pipeline Development

Design and build scalable ETL/ELT pipelines that automate data ingestion, transformation, and loading across your enterprise data ecosystem.

  • Batch and real-time data processing
  • Data quality and validation frameworks
  • Automated orchestration and scheduling
  • Error handling and monitoring

Data Lake Architecture

Build modern data lakes that centralize your data from disparate sources while maintaining governance and security.

  • Multi-zone data lake design
  • Schema-on-read capabilities
  • Data cataloging and discovery
  • Lifecycle management and optimization

Real-Time Streaming

Implement streaming data platforms for real-time analytics, event processing, and immediate business insights.

  • Event streaming architecture
  • Stream processing and analytics
  • Complex event processing
  • Real-time data integration

Data Warehouse Modernization

Migrate and modernize legacy data warehouses to cloud-native platforms for improved performance and scalability.

  • Cloud data warehouse migration
  • Schema optimization and redesign
  • Performance tuning and optimization
  • Cost optimization strategies

Data Integration

Connect and integrate data from multiple sources including databases, APIs, SaaS applications, and legacy systems.

  • API and database connectors
  • SaaS application integration
  • Legacy system connectivity
  • Change data capture (CDC)

Data Platform Engineering

Build end-to-end data platforms that support analytics, machine learning, and business intelligence at scale.

  • Cloud-native platform architecture
  • Multi-cloud and hybrid solutions
  • Self-service data access
  • Platform monitoring and observability

OUR APPROACH

How We Build Data Engineering Solutions

1. Discovery & Assessment

We analyze your current data landscape, identify pain points, and define clear objectives for your data engineering initiative.

2. Architecture Design

Design scalable, cloud-native architecture tailored to your specific requirements, data volumes, and performance needs.

3. Implementation

Build and deploy data pipelines, platforms, and infrastructure using industry best practices and proven methodologies.

4. Testing & Validation

Rigorous testing of data quality, pipeline performance, and system reliability before production deployment.

5. Deployment & Migration

Seamless deployment with minimal disruption, including data migration and cutover planning.

6. Optimization & Support

Ongoing monitoring, optimization, and support to ensure peak performance and reliability.

USE CASES

Common Data Engineering Scenarios

Customer 360 Platform

Unify customer data from CRM, marketing, sales, and support systems into a single source of truth for personalized customer experiences.

Real-Time Analytics

Build streaming data platforms that process and analyze events in real-time for immediate business insights and automated actions.

IoT Data Processing

Handle high-velocity IoT sensor data at scale for predictive maintenance, quality control, and operational analytics.

Data Warehouse Migration

Migrate legacy on-premises data warehouses to modern cloud platforms for improved performance and reduced costs.

Multi-Source Integration

Integrate data from databases, APIs, files, and third-party systems into unified analytics-ready datasets.

ML Data Pipelines

Build specialized pipelines for machine learning feature engineering, model training, and inference data delivery.

Ready to Build Scalable Data Infrastructure?

Partner with VarniViews to transform your data engineering capabilities. Schedule a free consultation to discuss your requirements.