Data engineering for reliable decisions

We build the data pipelines your business depends on.

We design and build reliable data ingestion and transformation pipelines that turn scattered data into clean, structured, business-ready information.

  • Databricks
  • Delta Lake
  • PySpark
  • SQL
  • Medallion Architecture
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Data sources flowing into Bronze, then through Silver and Gold layers to BI and analytics, AI and ML, applications and data products

What we deliver

Data engineering built for production.

From ingestion to curated data, we design, build and modernize the systems that move data reliably through your platform.

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Data Ingestion

Get data reliably from source systems into your platform.

APIs · Databases · Files · Events · Streaming

Data Transformation

Turn raw data into clean, structured information.

Validation · Enrichment · Deduplication · Modeling

Lakehouse Architecture

Structure data for maintainability, trust and scale.

Bronze · Silver · Gold · Metadata · Governance

Pipeline Engineering

Engineer pipelines for reliable operation in production.

Orchestration · Monitoring · Error handling · Data quality

Platform Modernization

Replace fragile processes with maintainable infrastructure.

Migrate · Automate · Optimize · Scale

How we build

From source
to trusted data.

A clear, structured approach to turn scattered data into a reliable foundation for analytics and AI.

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Source Systems
Databases
APIs
Files
Events
Ingestion
Ingest (batch, incremental
or streaming)
Auto LoaderCDCAPIsScheduling
Lakehouse (Medallion)
BronzeRaw
SilverClean
GoldBusiness Ready

Databricks · Delta Lake · Unity Catalog

Consumption
BI & Analytics
AI / ML
APIs
Data Products

Technical expertise

Built with modern
data engineering
technologies.

We combine modern data technologies with proven engineering practices to build scalable and maintainable data platforms.

Databricks

  • Lakehouse architecture
  • Workflows
  • Unity Catalog
  • Auto Loader

Delta Lake

  • ACID transactions
  • Schema evolution
  • Time travel
  • Incremental processing

Apache Spark

  • PySpark
  • Distributed processing
  • Scalable transformations
  • Batch and streaming

SQL

  • Data modeling
  • Transformations
  • Validation
  • Analytics

Engineering

Selected engineering work

Selected engineering work demonstrating architecture decisions, reusable patterns and production-oriented implementation.

Enterprise Data Validation Framework

Designed a configuration-driven Databricks validation framework to compare code-freeze pipeline output against production data, detect schema and data-level differences, and surface the impact of business-logic changes before release.

DatabricksPySparkSQLDelta Lake
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High-Performance Financial Data Pipeline

Optimized a SQL-based financial data pipeline with approximately 40 business rules sharing common intermediate results, reducing execution time by 45% through early filtering, improved join strategies and the removal of redundant processing.

DatabricksSQLPyTestPerformance Optimization
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Enterprise Data Platform Modernization

Migrated complete enterprise data pipelines from Snowflake and Airflow to Databricks using a controlled pipeline-by-pipeline strategy, Medallion Architecture and old-vs-new data validation.

DatabricksDelta LakePySparkMigration
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Retail Monitoring Data Warehouse

Designed and built a SQL Server retail data warehouse integrating multiple transactional MySQL systems, with near-real-time ingestion, a normalized snowflake model and operational reporting for approximately 60 business users.

SQL ServerT-SQLData WarehousingData Modeling
View project

Insights

Technical perspectives on modern data engineering

Designing Reliable Databricks Ingestion Pipelines

Key patterns and practical considerations for building robust ingestion frameworks.

Read insight

Bronze, Silver, Gold: What Each Layer Should Actually Do

Understanding the Medallion Architecture beyond the basic diagram.

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Full Load vs Incremental Load vs CDC

Choosing the right ingestion strategy for your source systems.

Read insight

About BGP Data Works

Specialized data engineering, without unnecessary complexity.

BGP Data Works focuses on the data foundation behind analytics and AI: ingestion, transformation, lakehouse architecture and production-grade data pipelines.

Our approach is engineering-led, transparent and practical. We focus on clear architecture, sound technical decisions and maintainable systems that teams can understand and operate. We work with organizations that need to build, modernize or strengthen their data platform — from ingestion pipelines to production-ready lakehouse architectures.

Contact

Have a data engineering project in mind?

Tell us about your data sources, pipelines or platform goals. We can start with a focused conversation about the right approach.

Let's talk

Reach us directly by email.

Email
contact@bgpdataworks.com