Data Pipelines
ETL pipelines, data warehousing and analytics infrastructure for data-driven decisions.
Overview
Your data is only valuable if it is clean, accessible and timely. We build pipelines that extract data from your operational systems, transform it into analysis-ready formats and load it into warehouses where your team can actually query it. No more asking engineering to pull a report. No more spreadsheet exports that are stale by the time they arrive.
Our pipelines handle everything from simple daily syncs between two systems to complex multi-source data warehousing with real-time streaming components.
Technical Details
ETL Architecture
Extract-Transform-Load pipelines with clear separation of concerns. Incremental loading that processes only changed records, not full table scans. Schema evolution handling so pipeline changes do not break downstream consumers. Data quality checks at every stage with automated alerting on anomalies.
Data Warehousing
Dimensional modeling for analytics-friendly data structures. Slowly changing dimension handling for historical tracking. Materialized views and pre-aggregations for common query patterns. Query performance optimization through proper partitioning and indexing strategies.
Streaming
Real-time data processing with Apache Kafka or AWS Kinesis for use cases that cannot wait for batch cycles. Stream processing with windowed aggregations and event-time handling. Exactly-once semantics for critical financial or transactional data. Backpressure management for variable-rate data sources.
Orchestration
Pipeline scheduling and dependency management with Airflow or Prefect. DAG-based workflow definitions with clear data lineage. Failure recovery with checkpoint-based restarts. SLA monitoring with alerting when pipelines miss their delivery windows.
Tech Stack
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Ready to talk about data pipelines?
Let us know what you are building. We will tell you exactly how we can help.
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