Mrudula Tanniru
Data Platform Engineer · Palantir Foundry Specialist
I turn complex enterprise data into intelligent, decision-ready systems — architecting ontologies, pipelines, and operational products that drive measurable business impact across fraud, pharma, capital markets, and insurance.
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About Me
7+ Years of Enterprise Impact
I'm a Palantir Foundry Data Platform Engineer with deep hands-on expertise across the full Foundry stack — from Ontology SDK and AIP Logic to Workshop applications and governed semantic KPI layers. I've delivered high-stakes data products across fraud intelligence, pharmaceutical operations, capital markets, and global insurance.
What sets me apart: I bridge engineering and business. I don't just build pipelines — I design systems that make entire organizations smarter and faster.
$15M+
Annual revenue impact
90%
Reduction in manual effort
40+
Stakeholders empowered
100%
GxP audit compliance
Skills & Expertise
A full-stack data engineering profile built for enterprise scale — from raw ingestion to governed analytics products.
Data Integration & Engineering
  • Palantir Foundry Pipeline Builder
  • Data Connections (REST API, Postgres, S3)
  • PySpark distributed transforms
  • Data Lineage, Health & Monitoring
Operational Applications & BI
  • Workshop, Quiver, Contour, Slate
  • AIP Logic & Scenario-Driven Analytics
  • Power BI (DAX, RLS), Tableau, Excel
  • Alerting & Workflow Automation
Programming & Cloud
  • Python (Pandas, NumPy, Matplotlib)
  • SQL, NoSQL, Java, PySpark
  • Azure (ADF, Synapse, Databricks)
  • AWS (S3, Glue, Lambda), CI/CD
Governance & Compliance
  • Multipass Zero-Trust RBAC
  • GxP-Compliant Regulated Environments
  • Dataset Validation Rules & Audit Lineage
  • Schema Contracts & Data Contracts
Professional Experience
7+ Years · 4 Companies · 4 Industries
1
Lowe's Companies, Inc. — Dec 2025–Present
Data Platform Engineer, Palantir Foundry (Fraud Intelligence)
  • Architected a Fraud Intelligence Ontology with entity-centric Object & Link Types — improving fraud detection by 80%
  • Saved 120 manual hours/week by embedding decision-ready metrics into Workshop applications
  • Mitigated revenue leakage via Alerting & Workflow Automation, saving an estimated $15M annually
  • Drove 70% increase in cross-functional platform adoption across 40+ active Foundry users
2
Novartis — Feb 2025–Dec 2025
Senior Analytics Engineer, Palantir Foundry Platform
  • Designed enterprise-wide Pharma Ontology unifying clinical, supply chain & commercial domains via Ontology SDK
  • Achieved 100% compliance during regulatory audits by enforcing GxP-grade Dataset Validation Rules
  • Accelerated decision turnaround by 80% using AIP Logic and Scenario-driven operational analytics products
3
State Street Corporation — Sep 2024–Feb 2025
Business Intelligence Engineer, Palantir Alpha Platform
  • Modeled capital market entities supporting analytics for $150B+ in daily transaction volume
  • Improved reporting accuracy by 40% by standardizing semantic KPI definitions for 40+ stakeholders
  • Reduced upstream data errors by 50% via Data Lineage and validation rules across Alpha and Foundry environments
4
Infosys Ltd. — Jun 2019–Jul 2022
Data Engineer, Global Insurance & Reinsurance (P&C, Life & Annuity)
  • Architected Foundry Ontology unifying policy, claims & exposure data into a Golden Record
  • Reduced manual engineering overhead by 90% via automated validation frameworks in CI/CD pipelines
  • Slashed false-positive fraud alerts by 45% using Foundry graph analysis and AIP-driven thresholds
  • Automated 100% of regression suites, cutting testing cycles from 5 hours to <1 hour
Featured Projects
Enterprise-grade data products built on Palantir Foundry — each one a case study in engineering precision, business alignment, and measurable impact.
Fraud Intelligence Platform — Lowe's
Problem: Fraud teams relied on slow, passive reporting with no in-platform action capability.
Solution: End-to-end Foundry data product — Ontology, PySpark pipelines, AIP Logic, Workshop apps with Object Sets & Scenario logic.
Impact: 80% improvement in fraud detection · $15M annual savings · 120 manual hours reclaimed weekly
Palantir Foundry
AIP Logic
PySpark
Workshop
Pharma Ontology Unification — Novartis
Problem: Clinical, supply chain, and commercial data lived in fragmented silos with no unified entity model.
Solution: Enterprise-wide Pharma Ontology via Ontology SDK with GxP-compliant validation rules, schema enforcement, and semantic KPI layer.
Impact: 100% audit compliance · 80% faster decision turnaround · Zero data breaches
Ontology SDK
GxP Compliance
Pipeline Builder
Multipass
Capital Markets Analytics — State Street
Problem: $150B+ in daily transaction volume required auditable, real-time risk and liquidity analytics with zero reporting inconsistency.
Solution: Entity-centric Foundry Ontology for Trade, Portfolio & Market entities with strict Data Lineage and standardized KPI definitions.
Impact: 40% reporting accuracy improvement · 50% reduction in upstream data errors
Palantir Alpha
Python/SQL
Data Lineage
Risk Analytics
Insurance Data Platform — Infosys
The Challenge
A global P&C and Life & Annuity insurer needed a single, reliable data foundation to support actuarial analytics, fraud detection, and claims processing — across millions of policies, with zero tolerance for data loss during catastrophe cycles.
Key Outcomes
90%
Manual Overhead Cut
45%
Fewer False Fraud Alerts
10K+
TPM Processed
Approach & Architecture
Golden Record Ontology
Unified policy, claims, and exposure datasets into a single entity-centric source of truth using Palantir Foundry Ontology.
High-Scale Pipelines
Developed Spark/Python transforms enforcing data contracts — 100% reliability for downstream actuarial analytics.
Automated Validation & CI/CD
Integrated Data Health Monitors into CI/CD pipelines, eliminating manual engineering overhead and reducing testing cycles from 5 hours to under 1 hour.
Legacy-to-Cloud Migration
Led full migration of core insurance modules to cloud with 100% test coverage across policy lifecycle, claims, and reinsurance settlement.
How I Think
My approach to every data problem follows a consistent framework: understand the business, design the system, validate rigorously, and drive adoption. Engineering without business alignment is just overhead.
This cycle is what turns a technical deliverable into a business asset. I don't ship pipelines — I ship outcomes. Every engagement starts with the business question and ends with measurable change.
Impact by the Numbers
Across 7+ years and four industries, the results speak clearly.
$15M+
Annual Revenue Saved
Via automated alerting and fraud risk mitigation at Lowe's
90%
Manual Effort Eliminated
Across pipeline automation and CI/CD validation frameworks
80%
Faster Decision Turnaround
Through embedded AIP Logic and Scenario-driven analytics at Novartis
40+
Stakeholders Empowered
Daily-use Foundry Workshop applications adopted across cross-functional teams
$150B+
Daily Transaction Volume
Supported by capital markets analytics infrastructure at State Street
100%
Regulatory Audit Compliance
GxP-grade governance across all Novartis regulated workflows
Education
Graduate Degree
Northeastern University
Master of Science — Data Analytics Engineering
Concentration across Computer Science, Machine Learning & AI, Data Science, and Statistics. A rigorous technical foundation that underpins every architectural decision I make in production systems.
Core Competencies
What the Degree Unlocked
Machine Learning & AI
Predictive modeling, anomaly detection, and AIP Logic applied in production fraud and risk contexts.
Statistical Analysis
Rigorous analytical thinking applied to KPI design, forecasting accuracy, and business intelligence.
Distributed Systems
PySpark, cloud infrastructure, and scalable data architecture at enterprise scale.
Let's Connect
I'm always open to conversations about high-impact data engineering roles, Palantir Foundry platform opportunities, or challenging problems worth solving. If my work resonates with what you're building — reach out directly.

📬 Open to senior and staff-level roles in Data Platform Engineering, Palantir Foundry Architecture, and Analytics Engineering. Have deep knowledge in industries like fraud intelligence, Insurance, financial services, pharma and healthcare services, Retail and enterprise-scale data products.
If you're a staffing agency recruiter, please provide your E-Verify number. I prefer connecting directly with hiring companies.
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