End-to-End Data Management
Data is only valuable when it flows reliably from source to insight. We design and operate the full data lifecycle — from ingestion and transformation to storage and delivery. Whether you need batch ETL, real-time streaming, or a modern lakehouse architecture, we build pipelines that are robust, observable, and maintainable.
What We Build
ETL / ELT Pipelines
Automated data pipelines with Apache Hop, dbt, Airflow, and custom Python. Schema evolution, data quality checks, and lineage tracking built in.
Data Lakes & Lakehouses
Scalable storage on S3, ADLS, or HDFS with Delta Lake, Iceberg, or Hudi for ACID transactions and time travel on your data lake.
Real-Time Streaming
Apache Kafka and Confluent Platform for event-driven architectures. Schema Registry, ksqlDB, and Connect for reliable stream processing.
Data Warehousing
Dimensional modeling, slowly changing dimensions, and analytics-ready schemas in BigQuery, Snowflake, Redshift, or on-prem solutions.
Tools & Platforms
We work across the modern data stack:
- ✓ Apache Hop — Visual ETL/ELT design, metadata-driven pipelines, and workflow orchestration
- ✓ Kafka & Confluent — Event streaming, Schema Registry, ksqlDB, connectors for 200+ systems
- ✓ Data Quality — Great Expectations, dbt tests, and custom validation frameworks
- ✓ Orchestration — Apache Airflow, Prefect, and cron-based scheduling with alerting