Data Engineering & Analytics
Modern data lakes, real-time streaming, and analytics platforms that turn raw data into insights.

Overview
Our data engineering practice builds the foundation for every AI initiative — unified, governed, and real-time data platforms that power analytics at scale. We architect cloud-native data lakes, streaming pipelines, and self-service BI environments.
Capabilities
- Cloud data lake and warehouse architecture (Snowflake, Databricks, BigQuery)
- Real-time streaming with Kafka, Flink, and Spark
- ETL/ELT pipeline design and orchestration
- Data governance, cataloging, and quality frameworks
- Executive dashboards and self-service analytics
- Data mesh and federated governance models
Use Cases
- Unified customer data platform for 360° views
- Real-time supply chain visibility dashboards
- Regulatory reporting and compliance analytics
- IoT sensor data ingestion and processing
Delivery Process
Discover
Stakeholder workshops, requirements analysis, and success metrics definition.
Design
Solution architecture, UX flows, security review, and delivery roadmap.
Develop
Agile sprints with continuous integration, code review, and quality gates.
Deploy
Cloud-native rollout on Azure with monitoring, documentation, and handover.
Optimize
Performance tuning, model retraining, and ongoing support SLAs.
Frequently Asked Questions
Discovery and MVP delivery typically range from 8–16 weeks depending on scope. Enterprise rollouts may extend to 6–12 months with phased delivery.
Yes. We integrate with ERP, CRM, data warehouses, and legacy platforms. Our teams specialize in hybrid and cloud migration scenarios.
We serve healthcare, finance, manufacturing, retail, logistics, telecom, and insurance with domain-specific accelerators.
We offer fixed-scope projects, time-and-materials, and managed services retainers. See our Pricing page for engagement models.
Bavanex operates from Belgium, Netherlands, Serbia, and Chennai with hybrid and remote delivery models for global clients.
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