Practical analytics engineering skills demonstrated through hands-on projects.
Designing staging → foundation → marts transformations using dbt with clear layer responsibilities and analytical data modeling principles.
Implementing Kimball-style star schema models, including Slowly Changing Dimension (SCD Type 2), to create reliable analytical datasets.
Building deterministic batch pipelines that transform raw data into analytics-ready warehouse tables.
Scheduling and managing data pipeline workflows using Apache Airflow with retry handling and monitored DAG runs.
Applying structured validation checks and dbt tests to detect inconsistencies and protect analytical data contracts.
Structuring SQL transformations in modern analytical databases such as Snowflake and PostgreSQL.
My go-to stack for data engineering pipelines
An end-to-end analytics engineering simulation for a SaaS subscription business, implementing layered transformations, dimensional modeling, and resilient data ingestion across …
A reproducible analytical ETL pipeline with explicit data contracts, star schema modeling, and enforced data quality gates.
Phase 4: Cloud Infrastructure & Automation
Phase 3 of my data engineering journey focused on moving beyond local experimentation and into a cloud-based analytics pipeline, while learning how to work within real-world …
Phase 2 of my data engineering journey was all about putting theory into practice by building an end-to-end data pipeline project while learning why architectural decisions matter …
Let’s build something amazing together
I'm always interested in hearing about new projects and opportunities. Whether you're looking to hire, collaborate, or just want to say hi, feel free to reach out!
I’m currently looking for Analytics Engineer or Data Engineer roles.
Let’s connect and discuss how I can help your team.