A. Donovan Contact →

AugustineDonovan

Analytics Engineer Data · Systems · Automation

I sit at the cornerstone of Business and Engineering. Designing solutions end-to-end, from the pipeline to the data model to the dashboard, and all the infrastructure running quietly behind it all.

Current
Interchecks TechnologiesData Insights Group · 2 yrs
Previously
Goldman SachsCredit Risk Analytics & Reporting · 3.5 yrs
Education
Master of Science in Business AnalyticsUC San Diego · BA Mathematics & Economics · UC Santa Cruz
Technical Range
SQL · Python · TableauGitHub Actions · Terraform · AWS · Snowflake
§ 01

Skills

Applied
Languages
SQL Python
Cloud & Infrastructure
AWS Redshift AWS Lambda AWS S3 AWS IAM AWS EventBridge Snowflake Terraform GitHub Actions CI/CD boto3
Data & Analytics
Tableau Pandas NumPy Polars scikit-learn XGBoost Seaborn Matplotlib Selenium
Tooling
Claude Code Git VS Code DataGrip Flyway Migration Jira Confluence Trello
Domain Knowledge
Orchestration & Pipelines
Dagster Docker dbt ETL/ELT
ML & Statistics
Linear Regression Logistic Regression Random Forests Neural Networks A/B Testing Hypothesis Testing Simulations
System Design
Data Pipeline Architecture Data Warehouse Design Workflow Automation Data Modeling ERD Design Repository Scaffolding Modular Codebase Design
Leadership
Strategy & Direction
Data Strategy Roadmap Design Tech Stack Selection Personnel Hiring Team Staffing & Organization
Stakeholder Management
C-Suite Product Risk Operations Engineering Third-party Vendors Clients Platform
Team Development
Mentored 10+ Team Members Deputy Head of Data Weekly Data Sync Bi-weekly Office Hours Monthly Team Newsletter Cross-functional Collaboration Agile · Kanban
§ 02

Experience

Interchecks Technologies
Data Scientist | Data Insights Group
Jul 2024 – Present Fintech · Payments · Remote
  • Established a four-pillar data strategy (Descriptive, Diagnostic, Predictive, Prescriptive) with a Run/Build operating model. Drove targeted hiring of a data analyst and data engineer to staff each function.
  • Originated the Normalized Attempted Transaction (NAT) metric — the organization's first production-deployed derived metric. Deduplicates repeated consumer attempts to isolate true user intent. Reframed how executives and clients read product performance and shifted risk decisions from portfolio-wide intervention to precise tail-level action. No third-party vendor or industry peer had established this lens.
  • Built a production-grade AWS data automation platform (S3, Lambda, Redshift) giving the data team a version-controlled environment for Python workflows. Removed the infrastructure bottleneck that had capped data automation capacity.
  • Refactored core database view architecture. Cut SQL query latency from 70–90 minutes to 14 minutes — unblocking dashboard performance across the full reporting suite.
  • Built and maintains 20+ Tableau dashboards including 15 executive-level client reports. Fully branded, production-grade, covering 11–13M monthly transactions.
  • Runs 10+ automated Python workflows in daily production serving external supervisory reporting and internal application support.
  • Translates technical findings into executive decisions. Writes briefs for C-suite, product, risk, operations, and clients on what the data says and what to do about it.
  • Sets roadmap, specs, and delivery pace for an embedded data engineer. Projects include ETL pipeline design, nested JSON flattening, Redshift deduplication, and data modeling for new API endpoints.
SQL Python Tableau AWS ETL Data Strategy
Goldman Sachs
Associate | Credit Risk Analytics & Reporting
Associate Jan 2024 – Jul 2024
Analyst Jan 2021 – Dec 2023
Summer Analyst Jun 2020 – Aug 2020
Jan 2021 – Jul 2024 Finance · Risk · Salt Lake City, UT
  • Identified manual workflow bottlenecks across daily supervisory and internal monitoring obligations. Onboarded Query Plans and VS Code, saving the team ~25 person-hours per month.
  • Led implementation of 5 Objectives and Key Results (OKRs) focused on team efficiency and digital strategy adoption with minimal oversight.
  • Crafted 20+ interactive Tableau dashboards surfacing curated credit risk insights across the organization.
  • Built the analytical decks presented by the Managing Director and Senior VP to the FED, SEC, FINRA, S&P, Moody's, and Fitch. Developed 30+ data-driven narratives on a monthly and quarterly cycle.
  • Authored three global peer review and approval protocols for production dashboard and SQL data source deployments. Served as global lead for improving underperforming Tableau workbooks — identifying and prioritizing 6 assets per quarter to drive department-wide adoption.
  • Collaborated directly with a VP to design a counterparty credit risk stress test report for senior management. Aggregated multi-source datasets in Python and cut ETL refresh from several hours to 10 minutes.
  • Mentored junior and senior analysts across the team. Hosted bi-weekly office hours to surface automation opportunities for the regional data function.
SQL Python Tableau Credit Risk Regulatory Reporting Data Viz
§ 03

Education

Dec 2024
UC San Diego
MS · Business Analytics · Rady School of Management
3.75
GPA
Fraud Analytics · Supply Chain Analytics · Customer Analytics · Research Methods · Database Management · Natural Language Processing
Jul 2020
UC Santa Cruz
BA · Economics & Mathematics · Dept. Honors · Cum Laude
3.76
GPA
Real Analysis · Econometrics · Probability Theory · Mathematical Proofs · Linear Algebra · Economic Law · Financial & Managerial Accounting · Economic Growth · Economic History of the US · Security Markets & Financial Institutions · Corporate Finance · NCAA Athlete · SIEML Fellow

The data speaks.
So do I.

Get in Contact

Strongest in data-intensive environments where the work is expected to hold up under scrutiny.

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