Transforming Complex Data into High-Impact Enterprise Intelligence
Senior Data Science Engineer & Cloud Data Architect with deep expertise across Azure Data Lake Gen2, Synapse, Python/SQL, and Machine Learning. Proven history of optimizing foundry manufacturing pipelines at Intel Ireland, securing €315k in ML project funding at Uniquely, and automating hundreds of manual engineering hours.
class DataPlatformLeader:
engineer = "Shivtej Patil"
focus = ["Data Architecture", "MLOps", "Cloud Scalability"]
cloud_stack = "Azure Synapse + ADLS Gen2"
governance = "CIPM / GDPR / DPO"
def deliver_impact():
"intel_bottleneck_cut": "30%",
"hours_saved_daily": "16+ hrs",
"approved_ml_budget": "€315k"
}
Reduction in unnecessary lot prioritization via automated alerting & controls.
Approved by COO for end-to-end ML Sales Optimization platform as Product Owner.
Saved between SSIS-to-Azure migration (3-4h) and Power BI automation (13h).
Maintained across EU maps for autonomous navigation systems (HERE / Nokia).
How I Architect Enterprise Data Platforms
Click on any tier of the data lifecycle to explore the tools, design patterns, and systems I have implemented at Intel and Uniquely.
Ingestion & ETL
Heterogeneous data sources, automated triggers & fault tolerance.
Storage & Schema
Tiered ADLS Gen2 bronze/silver/gold with strict data governance.
Modeling & AI
Feature engineering, predictive modeling & defect classification.
BI & Compliance
Executive dashboards, automated alerts & CIPM/GDPR guardrails.
Production Code & Execution Sandbox
Inspect real engineering scripts authored for semiconductor fab control, cloud lakehouse ingestion, predictive ML, and CIPM privacy compliance—paired with interactive live execution outputs.
Enterprise Engineering Leadership
Over a decade of progressive impact spanning semiconductor manufacturing, data analytics consultation, spatial intelligence, and automated cloud platforms.
Intel Ireland
Current EngagementData Science Engineer
Identified production bottlenecks in fab processes. Championed and deployed an automated data-driven lot prioritization architecture with authorization controls and automated alerting, delivering an immediate 30% cut in unnecessary prioritizations.
Spearheaded modernization of defect data management systems to meet rigorous foundry business standards. Migrated disparate silos (Excel, JMP, Web Portals) into a centralized Azure Data Lake with Power BI and Plotly visualization.
Key engineering leader on the VIPRE initiative, consolidating Oracle, SharePoint, and SQL Server into an unified query interface, enabling cross-functional engineering teams to query and share high-volume telemetry seamlessly.
Audited scalability bottlenecks and migrated legacy on-prem SSIS packages to cloud-native Azure pipelines with automated alerting, saving the engineering team 3-4 hours every single day in manual maintenance and runtimes.
Uniquely
Senior Data Analyst
Abodoo
Data Science Intern
Engineered an econometric forecasting model predicting the demand for co-working and smart hub spaces in Ireland through 2030. This research directly influenced corporate strategy and provided key statistical inputs for Irish regional infrastructure and government planning.
HERE Solutions (Nokia)
GIS Analyst & Promoted to Senior Training Engineer
Achieved exceptional 98% spatial accuracy in geographical coding for European road navigation across 6 consecutive quarters using ArcGIS, Atlas, and Python scripting—critical for tier-1 automotive in-car navigation and ADAS systems. Promoted to Senior Training Engineer to mentor incoming engineers on lane topology and autonomous map development.
Highlighted Enterprise Solutions
Automated Lot Prioritization & Alerting Engine
Engineered authorization-backed automated alerting workflows that systematically identified fabrication production bottlenecks, eliminating human guesswork and reducing unnecessary priority requests by 30%.
Predictive Sales Optimization & Lead Scoring
Conceived, pitched, and owned the implementation of an end-to-end Machine Learning data platform that analyzed historical sales patterns, geolocation clusters, and customer propensity to score incoming leads.
VIPRE Unified Centralized Data Fabric
Collaborated in designing and maintaining a single-pane-of-glass data platform uniting disparate corporate data silos including Oracle, SharePoint catalogs, and SQL Server tables into an accessible semantic query layer.
Cloud Modernization: On-Prem SSIS to Azure
Assessed legacy pipeline vulnerability, latency, and hardware constraints. Executed lift-and-shift plus refactoring of on-premises SSIS packages to Azure Data Factory and Synapse, dramatically improving reliability.
Automated Multi-Client BI Reporting Engine
Replaced manual spreadsheet generation across 7 major enterprise clients with an automated Power BI semantic model, eradicating error-prone copy-pasting and recovering 13 engineering hours every single day.
Ireland Co-Working 2030 Predictive Model
Synthesized demographic shifts, internet broadband rollout, and employment trends to forecast long-term demand for regional co-working hubs throughout Ireland, steering capital allocation for public and private infrastructure.
Technical Proficiency & Toolset
Engineered for high-concurrency environments, data integrity, strict privacy compliance, and cloud cost efficiency.
Cloud & Lakehouse
Azure Ecosystem- Azure Data Lake Gen2 Enterprise
- Azure Synapse Analytics Advanced
- Azure Data Factory (ADF) Orchestration
- Azure Pipelines / CI-CD DevOps
- SSIS / SSRS Modernization Migration
Databases & Warehousing
High-Concurrency SQL- Microsoft SQL Server T-SQL / Perf
- Oracle Database PL/SQL
- PostgreSQL Complex Queries
- Dimensional Modeling Star/Snowflake
- Git & Versioned Schemas Source Control
Languages & ML
Core Engineering- Python (Pandas, NumPy, Scikit) Advanced
- SQL (Query Optimization) Expert
- JSL (JMP Scripting Language) Semiconductor
- Lead Scoring & Classification ML Models
- Time-Series Demand Forecasting Projections
Visual Analytics & BI
Actionable Dashboards- Power BI (DAX, Modeling, RLS) Expert
- Plotly & Seaborn Interactive
- JMP Statistical Discovery Defect Analytics
- Tableau Visual Insights
- Advanced Excel Modeling Financial / Pivot
Leadership & Product
Execution & Strategy- Product Ownership (€315k CapEx) Owner
- Engineering Team Mentoring Lead
- Cross-Functional Stakeholders C-Suite / Ops
- Bottleneck Root-Cause Auditing Fab Process
- Agile / Scrum Sprint Management Delivery
Next-Gen AI & Productivity
Accelerated Velocity- Gemini AI Studio & LLM Prompting Advanced
- GitHub Copilot Code Acceleration Daily
- PMI GenAI for Project Managers Certified
- ChatGPT Automated Scripting Integrated
- CIPM Data Protection Guardrails GDPR Compliant
Certifications & Governance
A rare synthesis of deep cloud architecture and certified Data Protection Officer (DPO) privacy governance.
CIPM Training for Data Protection Officer (DPO)
IAPPFormal training completed under the International Association of Privacy Professionals (IAPP). Enables designing cloud architectures with built-in GDPR compliance, privacy-by-design, data subject access request (DSAR) workflows, and role-based data anonymization.
Microsoft Certified in Azure Fundamentals
Microsoft Cloud Core Architecture & Services
Microsoft Certified Professional (MCP) & MTA
Microsoft Technology Associate Engineering
Generative AI Overview for Project Managers
Project Management Institute (PMI)
Higher Education
Rigorous grounding in analytics theory, computer application design, and distributed computational logic.
Master of Science (MS) in Data Analytics
National College of Ireland (NCI)
Specialized in big data architectures, predictive statistical models, machine learning algorithms, and enterprise business intelligence frameworks.
Master's in Computer Application (MCA)
University of Pune
Advanced software engineering, database normalization, relational schema design, network architecture, and object-oriented systems.
Bachelor of Science in Computer Science
University of Mumbai
Core algorithms, data structures, computational mathematics, SQL systems, and software lifecycle principles.
Let's discuss how I can scale your data infrastructure.
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