Big Data Engineering
Pipelines that move and process data at scale.
We design data platforms that collect, stream, store and process large volumes of data reliably, so analytics, reporting and AI run on data you can trust. From event streaming to warehouses and lakehouses, we build and operate the pipelines.
In short
Aiwalay provides big data engineering for businesses worldwide. Pipelines that move and process data at scale. Services include streaming pipelines, batch processing and etl, data warehouses and lakehouses and more, built with Apache Kafka, Apache Spark, Apache Airflow. Every engagement starts with a free consultation, is scoped and priced in writing before work begins, and you own what we build.
What we offer
Streaming pipelines
Real-time event and IoT data ingestion with Kafka and stream processing.
Batch processing and ETL
Scheduled, monitored pipelines with Airflow, Spark and dbt.
Data warehouses and lakehouses
BigQuery, Snowflake, Redshift or PostgreSQL, modelled for fast analysis.
Data quality and governance
Validation, lineage, access control and documentation.
Feature stores for AI
Clean, versioned data ready for machine learning and AI agents.
Migration and modernisation
Moving from legacy databases or Hadoop clusters to managed cloud services.
Technologies we use
How we work
- Consultation: a free discussion of your goals and current systems.
- Proposal: scope, timeline and a fixed price before work begins.
- Build and test: regular demonstrations and testing on real scenarios.
- Launch and support: handover, training and optional ongoing support. You own the result.
Big Data: frequently asked questions
Do we need big data tools?
Not always. If a well-designed database and scheduled jobs will do, we will recommend that. Streaming and distributed processing make sense when volume, speed or variety demand them.
Can you work with our current cloud provider?
Yes. We build on AWS, Google Cloud or Azure, using managed services where they reduce operating cost and effort.