Case Study - Powers ENGIE's Data-Driven Transformation with Serverless Data Lake Architecture

Supporting a Strategic Shift to Data-Driven Marketing

ENGIE, one of Europe's leading energy providers, is committed to the responsible growth of its power, gas, and energy services businesses while driving the transition to a low-carbon economy. As the leading electricity provider in Belgium, ENGIE focuses on four key areas: natural and renewable gas, renewable electricity, energy efficiency, and digital technologies.

Within ENGIE, the Marketing and Sales (M&S) department is responsible for all commercial activities development, with a mandate to maintain the company's position as Belgium's reference for electricity and gas while capitalizing on opportunities presented by the energy transition.

To strengthen their competitive edge and enhance customer engagement, ENGIE's M&S leadership recognized the need to transform into a data-driven organization. This strategic shift required a robust data infrastructure that could:

• Ingest, process, and analyze diverse data streams from multiple sources
• Scale seamlessly to accommodate growing data volumes and evolving analytical needs
• Ensure compliance with stringent GDPR requirements and ENGIE Group's security standards
• Deliver insights to marketing teams efficiently while minimizing operational costs

The M&S department faced particular challenges with siloed data sources, inconsistent data quality, and limited ability to derive actionable insights—all while needing to adhere to strict enterprise governance requirements and budgetary constraints.

A Serverless Data Platform Designed for Enterprise Needs

Necko Technologies designed and implemented a comprehensive data lake solution for ENGIE Marketing & Sales that addressed their specific requirements while adhering to enterprise standards. Our approach was grounded in three core principles:

1. Serverless-First Architecture

We built the entire solution on AWS serverless technologies, eliminating the need for server provisioning, maintenance, or capacity planning:

• Designed a multi-layer data architecture that separated raw data, processed data, and analytical outputs
• Implemented event-driven processing pipelines that automatically scale with data volume
• Created data transformation workflows that efficiently handle both batch and real-time processing needs

2. Enterprise-Grade Security and Compliance

We integrated rigorous security measures and compliance controls throughout the solution:

• Implemented fine-grained access controls at all layers of the data lake
• Designed automated data lifecycle policies for retention and deletion in accordance with GDPR
• Built comprehensive audit logging and monitoring to track all data access and transformations
• Incorporated data masking and anonymization capabilities for sensitive information

3. Infrastructure as Code with CI/CD Integration

To meet ENGIE's internal regulations and ensure operational excellence:

• Developed the entire infrastructure using CloudFormation templates
• Implemented CI/CD pipelines for automated testing and deployment
• Created comprehensive documentation and knowledge transfer materials
• Established monitoring dashboards and alerting for operational visibility

A Scalable, Secure Data Ecosystem

The solution we architected for ENGIE incorporates multiple layers to address different aspects of their data management needs:

Data Ingestion Layer

• Implemented multiple ingestion pathways including S3 uploads, APIs, and scheduled imports
• Created secure data transfer mechanisms for external partner data
• Developed data validation processes to ensure quality and consistency

Storage and Processing Layer

• Utilized Amazon S3 as the foundation for the data lake, with optimized partitioning for cost and performance
• Implemented AWS Lambda functions for data transformation, validation, and enrichment
• Created orchestrated workflows with AWS Step Functions to manage complex data processing sequences
• Deployed containerized processing for compute-intensive transformations using AWS Fargate

Analytics and Access Layer

• Deployed Amazon Athena for SQL-based analysis of large datasets
• Implemented connectivity to dashboarding tools for business users
• Created secure API access for integration with marketing tools
• Established role-based access controls for different user personas

Governance and Monitoring Layer

• Implemented comprehensive CloudWatch monitoring and alerting
• Created automated data quality assessment workflows
• Established data cataloging and metadata management
• Deployed security scanning and compliance verification processes

Enabling Data-Driven Marketing Innovation

The serverless data lake platform delivered by Necko Technologies has transformed ENGIE Marketing & Sales' capabilities:

Enhanced Analytical Capabilities

The marketing team can now access unified customer data, campaign performance metrics, and market insights through intuitive dashboards, enabling more targeted and effective campaigns.

Operational Efficiency

With fully managed services handling infrastructure concerns, ENGIE's team can focus on deriving insights and driving innovation rather than managing servers or worrying about system capacity.

Significant Cost Optimization

The serverless architecture dramatically reduced costs compared to traditional infrastructure, with the pay-per-use model ensuring ENGIE only pays for the resources they actually consume.

Accelerated Time-to-Insight

New data sources can be integrated in days rather than weeks, and marketing analysts can access processed data much more quickly, reducing the time from question to insight.

Enterprise Compliance by Design

The solution's built-in governance features ensure continuous GDPR compliance and adherence to ENGIE Group's security standards, minimizing regulatory risk.

Expanding Data-Driven Capabilities

Building on the successful implementation of the data lake, Necko Technologies continues to partner with ENGIE on several initiatives:

Advanced Analytics Integration

We're exploring the integration of Amazon SageMaker to enable machine learning capabilities for customer segmentation, churn prediction, and campaign optimization.

Real-Time Marketing Enablement

Plans are underway to expand real-time data processing capabilities to support dynamic, personalized customer interactions across digital channels.

Cross-Departmental Data Sharing

The architecture is designed to facilitate secure data sharing with other ENGIE business units, creating opportunities for enterprise-wide insights while maintaining appropriate access controls.

Expanded Self-Service Capabilities

We're developing additional self-service tools to empower business users to create their own reports and analyses without requiring technical assistance.

AWS Services Used