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Title Line
Developer | Stack Technologies Ltd. | Jun 2025 - Present
Role Summary
Building and enhancing StackDX's data platform capabilities, focusing on a scalable data orchestration and data engineering platform well suited for billions of rows of data across thousands of sources.
Key Achievements (Bullets)
- Architected and implemented production-grade Dagster/dbt pipeline processing USA oil & gas data across 15+ states with 400+ transformation models, replacing legacy Python-based ETL processes with maintainable modern data stack. All Open Source & Self-Hosted. - Reduced processing time by up to 98% for critical datasets through strategic use of Polars, DuckDB, and optimized data modeling patterns - Designed and deployed AWS cloud infrastructure using Terraform, managing RDS PostgreSQL, ECS compute clusters, and S3 data lakes across staging and production environments - Implemented comprehensive CI/CD workflows with GitHub Actions, automated validation (formatting, linting, type checking), and multi-environment deployment strategies - Developed reusable framework patterns to standardize data pipeline development, reducing boilerplate code and ensuring consistency across 100+ data assets - Established software development best practices including schema contracts, comprehensive testing, type-safe code, detailed documentation, and collaborative Git workflows for enterprise-grade reliability
Detailed Highlights (with categories)
Modern Data Platform Architecture: - Architected and implemented production-grade Dagster/dbt pipeline processing USA oil & gas data across 15+ states with 400+ transformation models, replacing legacy Python-based ETL processes with maintainable modern data stack. All Open Source & Self-Hosted. - Reduced processing time by up to 98% for critical datasets through strategic use of Polars, DuckDB, and optimized data modeling patterns Cloud Infrastructure & DevOps: - Designed and deployed AWS cloud infrastructure using Terraform, managing RDS PostgreSQL, ECS compute clusters, and S3 data lakes across staging and production environments - Implemented comprehensive CI/CD workflows with GitHub Actions, automated validation (formatting, linting, type checking), and multi-environment deployment strategies Software Engineering Excellence & Team Collaboration: - Developed reusable framework patterns to standardize data pipeline development, reducing boilerplate code and ensuring consistency across 100+ data assets - Established software development best practices including schema contracts, comprehensive testing, type-safe code, detailed documentation, and collaborative Git workflows for enterprise-grade reliability
Full Description (Summary + Achievements)
Building and enhancing StackDX's data platform capabilities, focusing on a scalable data orchestration and data engineering platform well suited for billions of rows of data across thousands of sources. - Architected and implemented production-grade Dagster/dbt pipeline processing USA oil & gas data across 15+ states with 400+ transformation models, replacing legacy Python-based ETL processes with maintainable modern data stack. All Open Source & Self-Hosted. - Reduced processing time by up to 98% for critical datasets through strategic use of Polars, DuckDB, and optimized data modeling patterns - Designed and deployed AWS cloud infrastructure using Terraform, managing RDS PostgreSQL, ECS compute clusters, and S3 data lakes across staging and production environments - Implemented comprehensive CI/CD workflows with GitHub Actions, automated validation (formatting, linting, type checking), and multi-environment deployment strategies - Developed reusable framework patterns to standardize data pipeline development, reducing boilerplate code and ensuring consistency across 100+ data assets - Established software development best practices including schema contracts, comprehensive testing, type-safe code, detailed documentation, and collaborative Git workflows for enterprise-grade reliability
Education Snippets
Skills Summary
All Skills (Grouped by Type)
Data & Software: - Data Visualization: Tableau, PowerBI, matplotlib, Seaborn, Plotly, D3.js, ggplot2, Dash, Bokeh, Spotfire - Data Engineering: SQL, dbt, Dagster, Snowflake, Snowpark, pandas, Tableau Prep, cube.js & dbt semantic layers - AI & LLM's: APIs [OpenAI, Claude, Perplexity], Editors & Tools [Windsurf, Cursor, Claude Code], Structured Outputs & Schema Adherance, Agent Frameworks [autogen, crew], RAG - Database Design, Implementation & Querying: Snowflake, MongoDB, Oracle, SQL Server, Hive, PostgreSQL, DuckDB - Machine Learning, Natural Language Processing & Deep Learning: scikit-learn, Tensorflow Keras, PyTorch, nltk, Hugging Face - Distributed Computing & Cloud: Snowflake, Spark, Hadoop, Databricks, Terraform, AWS, Google Cloud, Azure, Docker - Web App Development: React, node.js, Next.js, Astro, Directus, tailwindcss, express, Flask, Streamlit, Dash, Algolia, Vercel, Supabase, Railway - Graph Databases: neo4j, networkX - ML Ops: Snowflake & Snowpark, DataRobot, Tableau Programming Languages: - Programming Languages: Python, SQL, Javascript, Typescript, Bash, R Oil & Gas: - Upstream Oil & Gas Development: Exploitation/Development, Reservoir & Petroleum Engineering, Production Engineering, Operations, Corporate Reporting - Petroleum Reserves Evaluation: COGEH, NI 51-101