Advanced Data Engineering
Build efficient ETL processes, real-time data pipelines, and quality controls that produce accurate and timely insights for mission-critical products.
Reliable Pipelines, Useful Data
ETL, streaming, quality, orchestration — production-grade data engineering that your analysts trust.
ETL & ELT Pipelines
Batch and streaming pipelines, incremental loads, upsert patterns, late-arriving data handling, and schema evolution.
Build PipelineReal-Time Processing
Apache Kafka, Flink, Spark Streaming, RisingWave — event processing, windowing, aggregations, and materialized views.
Build PipelineData Quality & Testing
Great Expectations, dbt tests, schema validation, anomaly detection, data contracts, and SLA monitoring.
Build PipelineOrchestration & Scheduling
Airflow, Dagster, Prefect, Temporal — DAGs, dependencies, retries, backfills, and dynamic task mapping.
Build PipelineGitOps for Data
Version-controlled pipelines, CI/CD for data, automated testing, preview environments, and rollback procedures.
Build PipelineObservability & Lineage
Column-level lineage, freshness dashboards, cost attribution, performance profiling, and alerting.
Build PipelineFive-Step Pipeline Delivery
Data Source Assessment
Catalog sources, assess quality, define SLAs, and identify critical paths.
Pipeline Architecture
Design DAGs, select orchestration, define data contracts, and plan testing strategy.
Incremental Implementation
Build pipelines module by module, validate at each step, automate testing.
Quality & Load Testing
Chaos engineering, data diffing, performance benchmarks, and failure injection.
Monitoring & Optimization
Deploy observability, tune performance, document runbooks, and train team.
Fixed-Price Data Engineering
Per pipeline or platform. No volume surprises. GST (18%) extra.
Single Pipeline
- One ETL/ELT pipeline
- Orchestration setup
- Quality tests
- Monitoring
- 2-month support
Data Platform
- Up to 10 pipelines
- Shared orchestration
- Data catalog
- Lineage
- CI/CD
- 6-month support
Enterprise Platform
- Unlimited pipelines
- Multi-team
- Self-serve
- SLA
- Source code
- 12-month support
Have Questions?
Batch for hourly/daily loads with large volumes. Streaming for sub-minute freshness needs. We often start with batch and evolve to streaming as requirements grow.
Watermarks, allowed lateness windows, side outputs for late events, and backfill procedures. We design based on your business tolerance for completeness vs latency.
Yes. We extend existing Airflow/Dagster/Prefect deployments and dbt projects. We follow your conventions and improve what's there.
We implement data contracts, PII tagging, access controls, audit logs, and retention policies. GDPR, CCPA, HIPAA compliance built into pipeline design.
Partition pruning, incremental processing, spot instances, right-sizing, caching, and eliminating redundant computations. We provide cost dashboards.
Trust Your Data
1M+ events/day. <5min latency. 99.9% reliability. GitOps for data.