Ukiah Heasley
San Francisco,CA
Summary
Analytical and detail-oriented Data Professional with a strong foundation in data modeling, SQL, and Python, skilled at developing and maintaining ETL/ELT pipelines to ensure clean, reliable, and well-structured datasets for analysis. Proficient in applying machine learning and causal inference techniques to uncover insights, validate hypotheses, and drive actionable business decisions. Experienced in collaborating with cross-functional teams, including data scientists, engineers, and product stakeholders, to translate business needs into data-driven solutions and strategies. Passionate about leveraging modern analytics practices, cloud technologies, and automation to improve reporting, optimize performance, and empower organizational decision-making.
Overview
3
3
years of professional experience
Work History
Data Engineer
Provista Software corporation
Sacramento, CA
06.2023 - Current
- Designed and implemented the company's central data warehouse using star schema and dimensional modeling, adhering to best practices. This foundational architecture powered the company's entire analytical product, enabling efficient data processing and insights.
- Led a data migration initiative, enabling the client to transition from legacy software seamlessly. Managed stakeholder communications through regular project updates, aligned business processes with technical requirements, and ensured the team adhered to Agile best practices.
- Developed essential Power BI reports that drove customer adoption of the company's SaaS product, delivering actionable insights and enhancing user engagement.
- Maintained the CDC pipeline using Debezium, Kafka, and Snowflake, ensuring reliable real-time data streaming and integration.
Machine Learning Module Developer
UC Berkeley Computing, Data Science, and Society
Berkeley, CA
06.2022 - 01.2023
- Developed jupyter notebooks and curriculum for new courses at UC Berkeley. Focus on implementing core algorithms in Biology and natural language processing in Legal Studies.
- Collaborated with faculty on best practices for Data Science curriculum.
- Developed material that introduced to students how to collect, clean and visualize text data, build text features using vectorization and apply deep learning methods such as BERT for NLP tasks.
- Developed material to introduce students to asymptotic run time analysis and implementing dynamic programming algorithms to solve problems in computational biology.
Education
Bachelor of Arts - Economics, Data Science
University of California, Berkeley
Berkeley, CA05.2023
Skills
- Programing Languages: Python, SQL, Rust, Spark, PowerShell and Bash scripting
- Software Development: Git, Agile, Unit Testing
- Data Ingestion: AirByte
- Data Processing: DBT, DuckDB, Pandas, Polars
- Data Orchestration: Apache Airflow
- ELT/ETL Pipeline Design
- Dimensional Data Modeling: Star and Snowflake Schema
- Databases: SQL Server, Snowflake, Databricks, Postgres, MongoDB
- AWS: S3, Lambda, Athena, Redshift, Glue, DynamoDB, API Gateway
- Data Governance & Data Quality
- Data Visualization and Dashboards with PowerBI
- SQL Performance Optimization and Query Tuning
Projects
Data Warehouse & Performance Optimization in Postgres: Developed a data warehouse for the UC Berkeley campus using dbt-core and PostgreSQL. Analyzed query execution plans to optimize query performance across a variety of analytical workflows. Identified and implemented optimal indexing strategies and query tuning techniques.
Gitlet: Implemented the core functionality of version control software that mimics basic features of Git in Java. Developed Unit and Integration tests to ensure code quality.
Timeline
Data Engineer
Provista Software corporation
06.2023 - Current
Machine Learning Module Developer
UC Berkeley Computing, Data Science, and Society
06.2022 - 01.2023
Bachelor of Arts - Economics, Data Science
University of California, Berkeley
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