Peter Muriya Karanja

I'm Peter, an analytics data engineer who enjoys turning messy, disconnected data into something clear, structured, and useful.

SQL is at the core of my work, and I use it regularly to clean, transform, and analyze data. I'm comfortable working with CTEs, subqueries, joins, window functions, aggregations, and more complex queries when necessary. I also use Python when a task goes beyond what SQL is best suited for, from cleaning and reshaping datasets to building data pipelines and moving data between different systems.

I've worked hands-on with PostgreSQL, Snowflake, BigQuery, and dbt, which is the main tool I use for data modelling. I also build dashboards that turn analysis into insights that are easy to understand and act on. For version control and collaboration, I work with Git and GitHub.

Another area I've been having fun exploring is building AI agents with n8n. Most of what I've built so far has been for personal projects, where I get to experiment with automation and different ways of connecting systems. For example, I currently have a running workflow where an agent scrapes all the latest job postings and sends them to my Postgres. I'm still exploring what's possible, but I'd love to put that experience to work for a team that's curious about agentic AI.

Analytics Engineer, Data Science East Africa (Dec 2025 to Present)

• Transform multi-table source data into tested, production-ready data models using staging, intermediate, and mart layers.

• Develop reusable dbt macros to streamline data transformations and improve model consistency.

• Implement data quality tests to validate data integrity, accuracy, and reliability.

• Build and maintain GitHub Actions CI/CD workflows to automate testing and data transformation processes.

• Prepare reliable, structured datasets to support analytics, business reporting, and data-driven decision-making.

• Analyzed operational and project data to identify trends, performance gaps, and opportunities to improve workflow efficiency.

• Used SQL and PostgreSQL to organize, query, clean, and analyze business and project data.

• Built and maintained dashboards in Looker Studio to monitor key metrics and provide clear insights for decision-making.

• Tracked project performance, turnaround times, workload, quality metrics, and productivity to support day-to-day operations.

• Identified repetitive tasks and developed automation solutions and Chrome extensions to improve efficiency and reduce manual work.

• Used Git and GitHub to manage code, maintain projects, and support version control.

• Process and analyze over 100 minutes of market research interview data daily, working with diverse accents, audio quality, terminology, and business contexts.

• Develop a strong understanding of business operations, industry-specific terminology, and client requirements through exposure to interviews across different markets and industries.

• Transform unstructured interview data into accurate, structured, and client-ready transcripts while maintaining consistency and attention to detail.

• Perform quality assurance on transcripts produced by other editors, identifying omissions, inconsistencies, terminology errors, and data-quality issues before delivery.

• Research and validate technical terms, companies, products, and industry-specific entities using AI tools such as Gemini and Claude to improve data accuracy and contextual understanding.

• Apply systematic quality-control and validation practices to ensure information is complete, accurate, consistent, and aligned with project requirements.

• Bachelor of Science in Analytical Chemistry – Jomo Kenyatta University of Agriculture And Technology (2021-04)

• Data Engineering – LuxDevHQ Academy (2025-12)