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Open to Data Engineering & Analytics roles

Jacob McLean — Turning Data into Intelligent Decisions

Data Analytics Engineer with 3+ years designing scalable data pipelines and deploying AI-driven Generative BI. I reduced manual data processing time by 40% and improved forecasting accuracy by 15% with advanced statistical modeling.

Currently building with |

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Pipeline
Warehouse
Dashboard

About

Analytics engineering with an engineer's rigor

I build the layer between raw data and confident decisions — automated pipelines, tested models, and dashboards stakeholders actually trust.

Portrait of Jacob McLean, Data Analytics Engineer

Education

Michigan State University

B.S. in Mathematics · August 2024

East Lansing, MI

$ whoami

Jacob McLean — Data Analytics Engineer with 3+ years designing scalable data pipelines and deploying AI-driven Generative BI solutions in Python, SQL and Snowflake. I cut manual data processing time by 40% and improved forecasting accuracy by 15% through advanced statistical modeling, then surface the results in Power BI and Tableau.

$ focus --now

elt_pipelines · generative_bi · multi_agent_systems

Snippet · warehouse SQL

-- Monthly churn, retention and revenue KPIs
with monthly as (
  select
    date_trunc('month', event_ts) as month,
    count(distinct case when status = 'churned' then customer_id end) as churned,
    count(distinct customer_id)                                       as customers,
    sum(net_revenue)                                                  as revenue
  from analytics.fct_subscriptions
  where event_ts >= dateadd(month, -12, current_date)
  group by 1
)
select
  month,
  churned / nullif(customers, 0) as churn_rate,
  revenue,
  avg(revenue) over (order by month rows between 2 preceding and current row) as revenue_3m_avg
from monthly
order by month desc;

0+

Years Experience

0%

Manual Processing Time Cut

0%

Forecast Accuracy Gain

0M+

Records Analyzed

0

Public Repositories

Skills

The stack I build with

From ingestion to insight — languages, platforms and tools I use in production.

Languages

  • Python
  • SQL
  • R
  • LaTeX

Cloud & Big Data

  • AWS
  • GCP
  • Azure
  • Databricks
  • Hadoop
  • Spark

Data Engineering

  • ETL Pipelines
  • Apache Airflow
  • Kafka
  • dbt
  • Snowflake
  • Snowpark

Visualization

  • Tableau
  • Power BI
  • Excel
  • Streamlit

Libraries & ML

  • TensorFlow
  • PyTorch
  • Keras
  • Scikit-learn
  • Pandas
  • NumPy
  • SciPy
  • Matplotlib

Databases

  • MySQL
  • PostgreSQL
  • Microsoft SQL Server
  • Snowflake

Featured Projects

Pipelines, platforms and applied AI

Selected work spanning warehousing, streaming, BI and LLM-powered analytics.

Ecommerce Sales Analytics Dashboards

Interactive multi-view BI dashboard built on 5,000 ecommerce orders, covering executive KPIs, product performance and market/customer experience with revenue, order-value, delivery and satisfaction analytics.

Architecture

Order Data→SQL Modeling→Metric Layer→Dashboards
  • Executive overview with revenue, orders, AOV and customer KPIs
  • Annual and average monthly revenue trends
  • Category revenue mix, units sold and average order value comparison
  • Region–category revenue matrix with delivery and rating analysis

5,000

Orders analyzed

$5.11M

Net revenue

3

Dashboard views

SQLPythonPower BIData Modeling

Multi-Agent Sales Forecasting System

View Code

Full-stack agentic AI application orchestrating three specialized GPT-5.2 agents in sequence to analyze time-series business data and automate end-to-end sales forecasting and reporting.

Architecture

Business Data→Preprocess Agent→Forecast Agent→Report Agent
  • Sequential multi-agent orchestration with CrewAI
  • Autonomous data preprocessing agent
  • Time-series forecasting agent
  • Executive summary generation

3

Agents in pipeline

+15%

Forecast accuracy gain

2026

Year

PythonCrewAIScikit-learnSQLTypeScript

Modern ELT Data Warehouse on Snowflake

View Code

End-to-end production-style data engineering project demonstrating modern ELT architecture using Snowflake, Python, dbt, Snowpark and Streamlit.

Architecture

Raw Sources→Snowflake→dbt / Snowpark→Streamlit
  • Layered medallion ELT architecture
  • dbt models with tests and documentation
  • Snowpark transformations in Python
  • Streamlit consumption layer

3

Warehouse layers

ELT

Stack

Streamlit

Serving

SnowflakedbtSnowparkPythonStreamlit

Sales Analytics Dashboard

View Code

End-to-end sales analytics project using Python, Snowflake, SQL and Streamlit featuring ETL, star schema modeling and an interactive business dashboard across 9,994 Superstore line items.

Architecture

Source Data→ETL→Snowflake→Dashboard
  • ETL ingestion
  • Star schema modeling
  • KPI dashboard
  • Interactive filtering

9,994

Line items analyzed

$2.30M

Total sales

12.5%

Profit margin

PythonSnowflakeSQLStreamlit

End-to-End Retail Data Engineering Pipeline

View Code

Retail data pipeline covering ingestion, cleansing, transformation and analytics-ready modeling for downstream reporting.

Architecture

Retail Sources→Ingest→Transform→Analytics
  • Batch ingestion
  • Data cleansing
  • Dimensional modeling
  • Analytics-ready outputs

Retail

Domain

4

Stages

Batch

Mode

PythonSQLPandasETL

Fine-Tuning LLMs with Snowflake Cortex

View Code

Fine-tunes open-source LLMs such as Mistral-7B on proprietary data using Snowflake Cortex serverless AI, with scaled inference and a Streamlit app.

Architecture

Proprietary Data→Cortex Fine-Tune→Inference→Streamlit
  • Serverless fine-tuning
  • Proprietary data customization
  • Scaled inference
  • Interactive app

Mistral-7B

Base model

Cortex

Platform

Streamlit

Serving

Snowflake CortexMistral-7BPythonStreamlit

Databricks ETL Pipeline

View Code

ETL pipeline in Databricks that extracts raw sales data, applies cleaning and formatting transformations, and loads structured output for analysis.

Architecture

Raw Sales→Databricks→Transform→Curated Tables
  • Raw extraction
  • Cleaning & formatting
  • Structured load
  • Notebook orchestration

Spark

Engine

ETL

Pattern

Sales

Domain

DatabricksSparkPython

Experience

Three years shipping data products

Analytics engineering work measured by what shipped and what it changed.

Data Analytics Engineer

Feb 2023 — Present

McLean Telecom LLC · Remote

  • Designed and implemented automated data pipelines using Python, SQL and Snowflake, reducing manual processing time by 40% and improving data availability for executive dashboards.
  • Conducted exploratory data analysis on datasets exceeding 1M records with Pandas and Tableau, delivering insights that optimized digital platform performance and product strategy.
  • Developed and maintained monthly reporting frameworks in SQL and Power BI covering churn, retention and revenue KPIs.
  • Built advanced statistical and forecasting models that improved forecasting accuracy by 15% for marketing and operations planning.
  • Delivered data storytelling presentations and dashboards to non-technical stakeholders across departments.
PythonSQLSnowflakePandasTableauPower BI

Education

MSU

Michigan State University

B.S. in Mathematics · August 2024 · East Lansing, MI

GitHub & Metrics

Repositories and live KPIs

A snapshot of what I ship publicly, plus a sample operational dashboard from a production warehouse.

Languages

  • Jupyter Notebook · 47%
  • Python · 27%
  • TypeScript · 13%
  • R · 8%
  • SQL · 5%

Multi-Agent_Sales_Forecasting_System

Three GPT-5.2 agents orchestrating time-series forecasting

TypeScript

Modern-ELT-Data-Warehouse-on-Snowflake

Production-style ELT with Snowflake, dbt, Snowpark, Streamlit

Python

Sales_Analytics_Dashboard

ETL, star schema modeling and an interactive dashboard

Jupyter Notebook

AI-Powered-Call-Transcript-Analysis-App

Snowflake Cortex LLM analysis of support call transcripts

Jupyter Notebook

SMS-Spam-Detection-using-TensorFlow

Naïve Bayes, BiLSTM and USE transfer learning comparison

Jupyter Notebook

Credit-Card-Fraud-Detection

Fraud classifiers with trees, logistic regression and boosting

R

Live KPIs

-40%

Manual processing time

+15%

Forecast accuracy

1M+

Records analyzed

15

Public repositories

Contact

Let's build something with your data

Open to data engineering and analytics roles, freelance pipelines and dashboard work.

Based in Remote · United States

JacobmcL19@gmail.com

github.com/JacobmcL19 Email Resume