Databricks Lakehouse Ingestion & Medallion Architecture

Overview

Built and operated a Databricks Lakehouse ingestion and transformation framework on Delta Lake, implementing a Medallion Architecture (Bronze/Silver/Gold) to move data from raw landing through curated layers into analytics-ready datasets for reporting and KPI consumption.

Achievements

• Delivered production-grade Delta pipelines with incremental processing, schema consistency, and integrated data quality validation. • Improved KPI reliability and time-to-insight by standardizing raw-to-curated flows and enforcing consistent dataset definitions. • Increased operational stability through repeatable Databricks job execution, structured logging, and pipeline observability.

Responsibilities

• Owned Medallion pipelines end-to-end: Bronze ingestion (schema drift, metadata, partitioning), Silver curation (standardization, deduplication, rule enforcement), and Gold outputs (consumption-ready models and aggregations).
• Implemented upsert/incremental patterns using Delta Lake ACID capabilities where needed.
• Tuned Spark performance (partition strategy, file sizing, query optimization) to keep jobs efficient at scale.
• Partnered with stakeholders to translate reporting needs into curated tables and maintain shared metric definitions.