ProjectsLarge-Scale Distributed Data Pipeline
International Development / Data
Large-Scale Distributed Data Pipeline
Built a distributed data pipeline aggregating and processing data from 30+ heterogeneous sources for program monitoring and evaluation reporting.
ClientInternational Development Organization
Duration8 months
Team7 engineers
34
Data Sources Integrated
12M+
Records Processed Monthly
<5 min
Report Generation Time
98.5%
Data Quality Score
200+
Active Dashboard Users
Problem
Program data was scattered across 30+ different systems with inconsistent formats, update frequencies, and quality levels. Generating quarterly reports required weeks of manual data reconciliation. Decision-makers lacked timely access to program performance indicators.
Solution
We designed an ETL pipeline orchestrated by Apache Airflow, with custom adapters for each data source. A data quality framework automatically validates, cleanses, and reconciles incoming data. The processed data feeds a ClickHouse-based analytical layer that powers self-service dashboards and automated report generation.
Technology Used
Apache AirflowPythonClickHousePostgreSQLDockerKubernetesRedisGrafana
Impact
Reduced quarterly report generation from 3 weeks to under 5 minutes
Integrated 34 previously siloed data sources into a unified analytical layer
Achieved 98.5% data quality score through automated validation
Enabled real-time program monitoring for 200+ stakeholders
Architecture Highlights
Apache Airflow DAGs with dependency-aware scheduling and automatic retry logic
Custom data quality framework with configurable validation rules per source
Incremental processing with change data capture for efficient updates
Role-based access control on dashboards aligned with organizational hierarchy
Lessons Learned
Data quality automation must be built as a first-class concern, not an afterthought
Heterogeneous data source integration requires flexible adapter patterns with clear contracts
Stakeholder dashboards should be co-designed with end users to ensure adoption