Open to opportunities

Srinila Pogalla

Data engineer and analyst with experience shipping production pipelines, analytics warehouses, and ML-integrated data systems. Graduating December 2026, University of North Dakota.

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Who I am

I started in AI and data science out of curiosity — it was new, exciting, and full of possibility. I pursued a Bachelor of Engineering in Artificial Intelligence & Data Science at Stanley College of Engineering and Technology in Hyderabad, and somewhere along the way that curiosity became the foundation of everything I build today.

I made my way to the U.S., first to Florida Atlantic University and then to the University of North Dakota, drawn by research opportunities here. Grand Forks has been an unexpected home — the community, the people at UND, and the collaborative culture have shaped both the work and the person doing it.

Joining the Computational Research Center at UND was a turning point. I came in without a formal software engineering background and built my way up through hands-on work: full-stack development, MLOps, and production-deployed systems on a U.S. Department of Defense-funded Arctic research project. Outside of that role, I've independently built projects across NLP, RAG systems, agentic AI, ETL pipelines, and analytics warehouses.

Today I sit at the intersection of engineering and research — someone who can ship a containerized API and care about why a retrieval model underperforms on edge cases. I'm actively looking for roles in AI Engineering, Data Engineering, and Data Science where both of those things matter.

Where I've worked

Jan 2025 — Present
Graduate Research Assistant & Software Engineer
Computational Research Center (CRC), University of North Dakota · Grand Forks, ND
  • Contribute to design and development of full-stack decision support tools for Arctic and climate resilience research on a DoD-funded platform, working across the API layer, geospatial data services, and frontend integration.
  • Reduced geospatial processing time from ~40 minutes to ~4 minutes by replacing 896 individual Google Earth Engine API calls with 3 batch requests using sampleRegions(), then parallelizing downstream processing with Python multiprocessing across all available CPU cores — a 90% runtime reduction.
  • Extended and maintained FastAPI REST endpoints serving climate anomaly monitoring, wildfire prediction, freeze/thaw forecasting, active layer thickness estimation, and geospatial similarity search — all backed by Google Earth Engine-derived datasets.
  • Worked in a containerized production environment using Docker, Kubernetes, Rancher, and Helm; tested locally with kind clusters before deploying to production.
  • Built frontend interfaces connecting to backend data services using React, Next.js, and TypeScript.
  • Automated build, test, and deployment pipelines using GitHub Actions, maintaining reproducibility across distributed services.
  • Authored technical documentation on system architecture and operations, including reports on Kubernetes cluster integration, Apptainer runtime, Globus-based data transfer workflows, and NVIDIA Spark compute.
Technical Reports
Integration & Optimization of Kubernetes Cluster Apptainer Runtime Integration Globus-Based Data Transfer Workflows
Current role

Research publications

Preprint · 2025
ASAP: A Web-based Analysis and Decision Support System for Alaska Permafrost
Stephen Miller, Sheridan Parker, Srinila Pogalla, Andrew Wilcox, Timothy Pasch
ESSOAr · Earth and Space Science Open Archive · University of North Dakota
View on DOI ↗

Selected work

Agentic Analytics System
16 specialized AI agents on a ~100K-order PostgreSQL warehouse that answer business questions in plain English — catching metric drift (AOV returning two different values), 189 impossible-date records, and 789 duplicate review IDs before they reach analysis.
MCPClaude APIPostgreSQLAgentic AIPythonSQL
Hybrid RAG Framework for Climate Intelligence
Local RAG pipeline over 13 climate reports (338 chunks) using FAISS + BM25 hybrid retrieval, cross-encoder reranking, and Mistral 7B — achieving 94.62% citation support accuracy across 130 evaluated citations and 50% Recall@5 on a 28-question benchmark.
RAGFAISSPythonBM25LLMStreamlit
Context-Aware Autocorrect System
Three spelling correction architectures compared head-to-head across 8 metrics — TextBlob baseline, BERT MLM hybrid, and T5 seq2seq. T5 achieved CharAcc 93.88%, WordAcc 87.50%, and CER 0.0612.
BERTT5NLPTransformersPython
Airline Operations Analytics Warehouse
End-to-end analytics warehouse on 3.35M BTS flight records using Snowflake, a 4-layer dbt transformation pipeline, and a 6-page Power BI dashboard — all 23 data quality tests passing.
SnowflakedbtPower BISQLDAXDimensional Modeling
Automated Job Market Analytics Platform
Python ETL pipeline ingesting Adzuna job postings into a PostgreSQL star schema (2,647 postings, 899 companies, 725 locations) with 10 automated quality checks, 108-second end-to-end runs, and a 5-view Power BI dashboard for role, salary, and skill-demand analysis.
ETLPostgreSQLPythonPower BISQLAlchemyREST API
Border Crossing Dynamics
Ten Tableau visualizations analyzing U.S.–Canada and U.S.–Mexico land border crossings from 1996–2024, covering temporal trends and geographic patterns across 160+ ports of entry.
TableauData VisualizationEDAGeospatial

Beyond the classroom

AGU 2025 Annual Meeting, New Orleans
Conference · Research
AGU 2025 — American Geophysical Union Annual Meeting
Attended AGU 2025 in New Orleans as a presenting member of the UND ARCTIC Lab team. Shared the lab's work with the broader geoscience community, coinciding with the team's publication in AGU's JGR Machine Learning and Computation journal.
Grand Forks EDC Summer Intern Cohort
Community · Internship
Grand Forks EDC Summer Intern Cohort
Selected as part of the Grand Forks Economic Development Corporation's Summer Intern Cohort — a program connecting university interns with the local business community to build professional networks and contribute to regional economic engagement.

Credentials & licences

Analytics Engineering with dbt
dbt Labs
View certificate ↗
AWS Cloud Practitioner Essentials
AWS Training & Certification
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Mentors Helping Mentors
University of North Dakota
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AWS SageMaker & EKS
Amazon Web Services
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Data Classification and Summarization Using IBM Granite
IBM
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The AI Ladder: A Framework for Deploying AI in your Enterprise
IBM
View certificate ↗

Let's connect

I'm actively looking for internships, research roles, and full-time positions in AI Engineering, ML Engineering, Data Engineering, and Data Science. Whether you have something specific in mind or just want to talk — I'd love to hear from you.

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