CAREERS
Build the Platforms That Governed Analytics Runs On
On Point BI is a platform company, not a consultancy. The people who work here build and operate infrastructure that regulated enterprises depend on — and they are selected for exactly that.
We are building two proprietary platforms — Insight Ready Platform™ (IDPaaS) and Semantic Drift Intelligence™ — for healthcare, life sciences, pharma, financial services, and other regulated enterprises. The technical problems these platforms solve are genuinely hard: governed pipeline architecture at enterprise scale, semantic drift detection across SQL and AI systems, AKS-based microservices deployed inside client Azure tenants, and ML models that operate on semantically stable, audit-ready data. The people we bring onto this team are people who want to work on problems like these — and who have the depth to do it well.
WHAT WE BUILD
Two Platforms. Genuinely Hard Problems. Real Production Deployments.
On Point BI’s platforms are not consulting deliverables. They are proprietary, AKS-based products deployed in production inside regulated client environments — with governance, audit trails, semantic registries, and ML capabilities built into the architecture. The work here is platform engineering, data science, and governance design at enterprise scale. If that is the kind of work you want to do, this is the right place.
Azure Platform Engineering
AKS cluster deployment, infrastructure-as-code using Terraform and Bicep, Kubernetes workload management, Azure networking and identity configuration, Workload Identity Federation, and CSI Secret Store integration. Both IDPaaS and SDI run on AKS-based microservices architectures inside client Azure tenants.
Data Engineering and Pipeline Architecture
Bronze-to-Silver-to-Gold pipeline design, Azure Data Factory and Synapse Pipelines, semantic layer development, data quality validation, lineage capture, and governed data modeling. IDPaaS delivers this at production scale across multiple regulated client environments simultaneously.
Machine Learning and AI
Forecasting model development, anomaly detection, MLOps pipeline design, LLM integration within Azure OpenAI, and the drift detection engine at the core of Semantic Drift Intelligence™ — which combines deterministic rules, embedding-based comparison, and LLM reasoning to detect semantic inconsistency across SQL, BI, and AI systems.
Semantic Governance and Data Science
Semantic registry architecture, drift classification, governance workflow design, KPI definition management, and the organizational and technical work of making business definitions consistent, traceable, and defensible across SQL, BI, documentation, and AI environments.
WHAT WE VALUE
We Hire for Depth, Not Availability
On Point BI hires when we find exceptional people — not when a requisition opens. The team we are building is deliberately senior, deliberately small, and deliberately focused on the specific technical and domain expertise our platforms require. These are the things we look for.
Technical depth over broad familiarity
We work on problems that require genuine expertise — in Azure platform engineering, data science, semantic governance, or regulated-industry data architecture. Breadth is useful. Depth is required.
Governance thinking built in, not bolted on
Both platforms treat governance as an architectural principle, not a feature. The people who build them need to think the same way — designing for auditability, lineage, and compliance from the first decision, not the last.
Comfort with ambiguity at the frontier
Semantic drift as a product category did not exist before On Point BI named it. The people who thrive here are comfortable defining problems that do not yet have established solutions — and rigorous enough to solve them well.
Regulated industry awareness
Our clients are healthcare systems, pharma companies, CDMOs, and financial services organizations. Understanding what governance, compliance, and audit mean in those environments — not just in theory — makes the difference between a platform that satisfies procurement and one that does not.
Ownership over output
On Point BI is a platform company. The work does not end at delivery. The people here own what they build — through deployment, production operations, and continuous evolution.
We are building something that does not yet have many competitors — because most companies have not figured out how to define the problem yet.
If you have deep expertise in Azure data engineering, machine learning, semantic governance, or regulated-industry data architecture — and you want to work on problems that most companies are still trying to define — we want to hear from you. Roles open when we find the right people.
We hire when we find exceptional people, not when a requisition opens. If you have deep expertise in Azure data engineering, ML, or semantic governance and want to work on problems that most companies are still trying to define — we want to hear from you.