Ravi Shrestha
Other
0
Yrs Experience
Engineering Portfolio
Other
Data Engineer with 4 years building reliable data pipelines, warehouses, and analytics infrastructure at scale. I bridge the gap between raw data and business decisions — working closely with analytics, ML, and product teams.
- Designed and maintained a multi-source ELT pipeline ingesting 15GB+ of daily event data into Snowflake, cutting analyst query times from 40s to under 3s
- Migrated a legacy cron-based ETL system to Airflow DAGs with full observability, reducing pipeline failures by 80% and eliminating on-call incidents
- Built PipelineKit solo — an open-source CLI for scaffolding production-ready Airflow DAGs with built-in retry logic, alerting, and data quality checks
About
02I write pipelines like I write code — modular, tested, and documented. If an analyst can trust the data, the pipeline matters. Observability and data quality checks are first-class citizens, not afterthoughts.
Data Engineer with 4 years building and maintaining data infrastructure at scale using Python, Airflow, dbt, and Snowflake.
I started in analytics at a mid-size e-commerce company and kept getting pulled into the infrastructure side — fixing broken pipelines, rebuilding unreliable ingestion jobs, and wondering why the data was always wrong. Eventually I made it official. I've worked across retail, fintech, and SaaS, and I've learned that good data engineering is mostly about trust — making sure downstream teams can rely on what you ship.
Skills
Languages
3data engineering
4data warehousing
3databases
2tools & devops
4data quality
1data & ML
2All Projects
02.My Experience
Senior Data Engineer
Meridian Analytics — Seattle, WA
Senior data engineer on a 6-person data platform team at a Series B fintech company. Own core ingestion pipelines, the Snowflake data warehouse, and data quality infrastructure used by 30+ analysts and 3 ML engineers.
- 01Redesigned the company's core ELT architecture from ad-hoc Python scripts to a fully orchestrated Airflow + dbt stack, reducing data freshness SLA breaches by 90%.
- 02Built a data contract framework with Great Expectations that runs on every pipeline run — catching schema drift and volume anomalies before they reach downstream dashboards.
- 03Led a cross-functional initiative with analytics and product to define and document 80+ core business metrics in dbt, creating a single source of truth for company-wide reporting.
Data Engineer
Novu Commerce — Portland, OR
Data engineer on a two-person data team at a mid-size e-commerce company. Built and maintained pipelines for marketing, finance, and operations analytics.
- 01Migrated 14 legacy cron-based ETL jobs to Apache Airflow DAGs with proper retry logic, SLA monitoring, and Slack alerting — reducing weekly pipeline failures from 8-10 incidents to near-zero.
- 02Implemented a Snowflake data warehouse from scratch, consolidating data from Shopify, Stripe, Google Ads, and an internal PostgreSQL database into a unified analytics layer.
- 03Built a near-real-time inventory sync pipeline using AWS Lambda and DynamoDB Streams that reduced inventory discrepancy reports by 70%.
Academic Background
Education
B.S. Information Systems
University of Washington — Seattle
Data Engineering Nanodegree
Udacity
Contact
Making Data Teams Actually Trust Their Data
I'm currently open to senior data engineering roles at data-driven companies. If you're looking for someone who can build reliable pipelines, improve data quality, and work closely with analytics and ML teams — feel free to reach out.