Oil & Gas · E&P operator
Upstream Operations & VOC Monitoring Platform
SAP HANA + Spotfire pipeline for real-time production allocation and emissions tracking
View case study →Service
Data Engineering
Reliable pipelines and modern warehouses that make analytics trustworthy at scale.
Typical timeline · 10–16 weeks
Delivery architecture
ERP/CRM
Ingestion
Warehouse
dbt
Trusted data
01ERP/CRM
02Ingestion
03Warehouse
04dbt
05Trusted data
Delivery progress
Challenges
- Siloed source systems with no reliable integration layer
- Batch jobs that fail silently or deliver stale data
- No governed path from raw data to certified metrics
Outcomes
- Documented, monitored ingestion from critical systems
- Warehouse architecture designed for analytics workloads
- Certified datasets ready for BI and AI consumption
Engagement process
01
Discover
Map the decision, the systems that hold the data, and where the numbers disagree.
02
Design
Specify the model, the workflow, and the controls: approved data, permissions, and what a person must review.
03
Build
Implement pipelines, semantic models, dashboards, or analytical workflows in releases the team can review.
04
Validate
Check calculations, access, and outputs against agreed tests before a figure is treated as decision-ready.
05
Operate
Hand over documentation and, where you want it, stay on for monitoring and agreed improvements.
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Led by Ayush Dubey, Principal Data Platform & AI Consultant.