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Data Engineering & Integration

Data Engineering & IntegrationScalable pipelines powering real-time enterprise platforms.

We design, build, and migrate resilient data workflows — moving your business from brittle legacy SSIS batches to cloud-native ETL, event-driven pipelines, and continuous API integration.

Azure Data FactoryDatabricksAWS GlueApache KafkaEvent HubsAzure Logic AppsSSIS ModernisationMedallion ArchitectureCDC StreamingAzure Data FactoryDatabricksAWS GlueApache KafkaEvent HubsAzure Logic AppsSSIS ModernisationMedallion ArchitectureCDC StreamingAzure Data FactoryDatabricksAWS GlueApache KafkaEvent HubsAzure Logic AppsSSIS ModernisationMedallion ArchitectureCDC Streaming
Complex Data Integration Pipelines

Data value is defined by how well it flows.

Analytics and AI models are useless if they run on stale, incomplete, or disconnected data. We engineer self-healing, highly scalable integration pipelines that pull disparate structures into a unified operational platform—giving you confidence in the velocity and validity of your entire data estate.

Sound familiar?

  • Data pipelines are brittle and constantly fail without clear error alerting
  • Legacy SSIS packages cannot scale to handle modern data volumes
  • Business logic is tangled in undocumented, manual ETL processes
  • Crucial reporting data is always a day late due to overnight batch jobs
  • Disparate enterprise systems (ERPs, CRMs, SaaS) are disconnected and siloed
  • Engineering teams spend all their time fixing broken pipelines instead of building

What is included

  • Cloud-native pipeline architectures across Azure and AWS
  • Medallion (Bronze/Silver/Gold) data flow implementation
  • Legacy SSIS to modern ADF / Fabric migration
  • API, flat-file, database, and SaaS source integrations
  • REST and SOAP API middleware logic and routing
  • Event-driven and streaming pipeline patterns
  • Change Data Capture (CDC) and low-latency syncing
  • Automated error handling, retry logic, and alerting
  • Data lineage tracking for compliance and auditability
  • CI/CD pipeline versioning and documentation standards
Five Capabilities

Comprehensive Data Engineering & Integration

From source assessment and API routing down to event-driven streaming and SSIS modernization.

Data Pipeline Architecture
6–10 weeks
01

Data Pipeline Architecture

Design scalable, cloud-native pipeline architectures across Azure and AWS.

  • ADF, Databricks & AWS Glue pipeline design and build
  • Medallion (Bronze/Silver/Gold) data flow architecture
  • Event-driven and streaming pipeline patterns
  • Error handling, retry logic, and alerting configuration
  • Pipeline versioning and documentation standards
ETL / ELT Services
8–14 weeks
02

ETL / ELT Services

Efficient data migration and transformation to streamline data flows.

  • Complex business rule and data cleansing transformations
  • SSIS to ADF / Microsoft Fabric pipeline migration
  • ETL automation — scheduled and event-triggered workflows
  • Scalability solutions for growing data volumes
  • Data lineage tracking for compliance and auditability
Data Integration Solutions
6–12 weeks
03

Data Integration Solutions

Custom integration of disparate data sources into a unified system.

  • Source assessment — formats, structures, and compatibility
  • API, flat-file, database, and SaaS integration
  • Data mapping and standardisation across all sources
  • Implementation of integration orchestration frameworks
  • Before-and-after data flow documentation
API & System Integration
4–8 weeks
04

API & System Integration

Connect enterprise systems via APIs for seamless automated data flow.

  • REST and SOAP API integration architecture design
  • System-to-system data flow and middleware design
  • JSON / XML transformation and routing logic
  • Azure API Management and Logic Apps integration
  • Integration monitoring, alerting, and self-healing patterns
Real-Time Data Processing
8–12 weeks
05

Real-Time Data Processing

Low-latency, event-driven architectures for instant data availability.

  • Azure Event Hubs, Event Grid, and Kafka pipeline design
  • Streaming analytics with real-time insight delivery
  • Change Data Capture (CDC) from operational databases
  • Load management and elastic scaling for data spikes
  • Real-time anomaly detection and alerting pipelines
Automated Pipeline Architecture Migration
Case Study

National Retailer — Legacy SSIS Migration & Real-Time Sync

A nationwide retail brand struggled with delayed inventory reporting caused by failing overnight SSIS jobs. We architected a complete migration to Azure Data Factory utilizing Medallion Bronze/Silver/Gold transformations. We integrated Event Hubs for point-of-sale Change Data Capture (CDC), bringing inventory analytics from a 24-hour lag down to sub-minute latency.

99.9%
Pipeline Uptime
with self-healing retries
< 1 min
Data Latency
using CDC streaming
Zero
Manual Fixes
after ETL automation

Who this is for

Industries Served [cite: 11]

AutomotiveDefenceMiningRailClean EnergyHealthOil, Gas & EnergyTransport and LogisticsConstruction & EngineeringIT & CommunicationsProfessional ServicesWater

Target Roles

Head of Data EngineeringLead Data ArchitectChief Technology Officer (CTO)VP of EngineeringIT Integration Manager

Engagement Timeline

4–14 weeks

Depending on integration complexity and migration data volumes.

Architecture Output

Scalable & Versioned

We deploy entirely via CI/CD with robust orchestration frameworks, ensuring infrastructure as code (IaC) compliance.

Data Engineering & Integration

Stop fighting brittle data pipelines.

Book a 30-minute discovery session with our lead data architects. We will evaluate your current ETL bottlenecks, assess integration requirements, and propose a modern architectural blueprint.

Book a Pipeline Architecture Review