Data Engineer, Software Engineer

B L A K E G E A R D

D A T A E N G I N E E R

**********@*****.*** linkedin.com/in/blake-geard github.com/engineergrowth TECHNICAL SKILLS

Programming Languages: Python, SQL, Java, C#

Data Engineering & Analytics Tools: Pandas, Airflow, dbt, Kafka, PostgreSQL, SQLite Cloud Platforms & Services: AWS (S3, EC2, IAM, Lambda), GCP (BigQuery, GCS) Pipeline Design & Orchestration: ETL/ELT pipelines, data cleaning, schema design, pipeline automation, data warehousing, batch and streaming data pipelines Infrastructure & DevOps: Docker, Terraform, Git, CI/CD (GitHub Actions) PROFESSIONAL EXPERIENCE

Software Engineer Outlier.ai December 2024 - Present

• Developed and tested complex coding solutions to enhance the performance and reliability of AI systems for code generation and debugging.

• Wrote and executed extensive test cases, ensuring AI-generated outputs were accurate, logical, and ready for real-world scenarios.

• Contributed to the Hopper RLHF Project, creating and curating coding prompts to evaluate AI reasoning and decision-making across programming languages.

• Collaborated with cross-functional teams to refine AI models, improving user outcomes and ensuring deployment readiness.

• Tools: Python, JavaScript, GitHub, test frameworks, AI evaluation systems. Software Engineer / Founder Today’s Gig (Self-Directed Startup) December 2023 – October 2024

• Architected and developed a full-stack platform using Supabase and Next.js, connecting gig workers with businesses in a dynamic, scalable system.

• Designed and implemented a complex relational database schema, modeling multiple entities and optimizing data relationships across a dozen+ tables for user accounts, job posts, payments, and other business-critical data.

• Automated operational workflows using cron jobs for task scheduling. PROJECTS

DEHub – Data Engineering Hub

Designed and developed a collaborative open-source learning platform for aspiring data engineers.

• Created a comprehensive learning platform for aspiring data engineers, featuring foundational content across 7 sections: Python, SQL, ETL fundamentals, tooling, visualization and documentation.

• Designed and implemented 3 real-world pipeline challenges to teach hands-on skills in data ingestion, transformation, and orchestration.

• Nearing completion, with plans to launch as an open-source project to foster community-driven learning and collaboration.

Cloud-Native ETL Pipeline for Kindle Reviews

Designed and deployed a hyper-scalable, cloud-native pipeline to process and analyze 980K+ Amazon Kindle customer reviews, providing actionable insights with weekly updates.

• Data Ingestion: Automated ingestion of raw reviews from AWS S3 for seamless batch processing.

• Transformation: Leveraged dbt for efficient, scalable transformations in BigQuery, delivering insights into top products, trends, and new releases.

• Storage & Analytics: Optimized processed data storage in GCS and BigQuery for high-performance analysis.

• IaC: Provisioned GCS buckets and BigQuery datasets using Terraform for consistent, repeatable cloud deployments.

• Automation & CI/CD: Implemented CI/CD with GitHub Actions for DAG validation and automated Airflow updates.

• Orchestration: Built reliable, scalable Airflow DAGs to streamline pipeline performance. EDUCATION

• B.S. Software Engineering, WGU (Graduated Dec 2024)

• M.S. Data Engineering, WGU (Expected Feb 2025)

CERTIFICATIONS

• AWS Certified Cloud Practitioner (2023)

• Software Engineering Certificate, Fullstack Academy (2024)

• CompTIA Project+ (2022)

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