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Petabyte-Scale Data Platforms
Architect and build cloud data platforms that scale to petabytes.
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We design and build cloud data platforms engineered to handle petabyte-scale workloads — from high-throughput ingestion to governed, query-ready data. Whether you're modernizing a legacy warehouse or building greenfield on a lakehouse, we deliver an architecture that stays fast and cost-efficient as your data grows.
Every platform is built on engineering best practices: distributed processing with Spark, version-controlled transformations, automated orchestration, CI/CD, and observability — so the system is reliable, scalable, and easy for your team to extend.
What we do
- Lakehouse and cloud-warehouse architecture (Databricks, Snowflake, BigQuery)
- Distributed processing and large-scale ETL/ELT with Apache Spark
- Streaming and high-volume batch ingestion pipelines
- Partitioning, clustering, and query/cost optimization at scale
- Orchestration, CI/CD, and data observability
- Governance, security, and access control
What you get
- A production-ready platform proven at your data volumes
- Documented architecture and data models
- Cost and performance benchmarks with tuning guidelines
- Runbooks and knowledge transfer for your team