Data pipelines that break at 3 AM
Most enterprise data pipelines were built as one-off scripts — fragile, undocumented and impossible to debug when they fail at 3 AM. As data volumes grow and sources multiply, these pipelines become the weakest link in your analytics chain. Reports are delayed, dashboards show stale numbers, and data teams spend more time firefighting than building.
Modern data engineering requires proper architecture: schema management, lineage tracking, idempotent processing and observability. Without these foundations, every new data source makes the problem worse.
Assess & Architect
We audit your data landscape, map sources and sinks, and design a modern data architecture — lakehouse, data mesh or medallion — aligned with your analytics goals.
Build & Validate
Pipeline development with automated quality checks, schema evolution handling, and full data lineage. Every pipeline is idempotent and self-healing.
Monitor & Scale
Pipeline observability with alerting, SLA tracking and capacity planning. We ensure your data infrastructure scales with your business.
What we deliver
ETL/ELT pipelines for both batch and streaming workloads. Azure Data Factory, Apache Spark, Kafka and custom solutions — processing millions of records daily with full lineage tracking.
Modern data storage combining the best of data lakes and data warehouses. Delta Lake, Databricks or Azure Synapse — structured for analytics, ML and ad-hoc queries.
Connectors for any source: databases, APIs, files, SaaS platforms and IoT streams. Change data capture (CDC) for real-time replication without impacting source systems.
Schema registries, evolution policies and contract-first design. Data contracts between producers and consumers prevent breaking changes in production.
Automated data quality checks at every pipeline stage. Great Expectations, dbt tests and custom validation rules with alerting on anomalies.
Pipelines breaking overnight or data arriving late?
Talk to a data engineer who builds enterprise-grade ingestion at scale.
Anadolu Efes
Eight disconnected data sources feeding reports with conflicting numbers. No single source of truth for executive decision-making.
We designed a medallion architecture (bronze-silver-gold) with automated ETL pipelines, consolidating SAP and 7 other sources into a unified data platform.
Single source of truth. Report generation time cut by 60%. Real-time data visibility across 5 countries.
Where we apply it
- Modernize your data warehouse without disrupting live reports
- Stream database changes in real time with zero source impact
- Consolidate data from 10+ sources into a single platform
- Upgrade from data lake to lakehouse with ACID guarantees
- Ingest millions of IoT events daily without data loss
Technologies
Microsoft 
Cloudera