Cloud & Data
Data Pipelines & Integrations
Pipelines and connectors that move data reliably — batch, streaming, or event-driven.
12
Stack tools
11
Deliverables
Production
Focus
Focus
Cloud & Data
Production-ready delivery
Tech
KinesisS3AthenaWhat we build
Batch pipelines — Airflow DAGs, scheduled ETL, daily/weekly data loads
Streaming pipelines — Kafka, Kinesis, SQS-driven real-time processing
Data ingestion from any source — APIs, databases, file drops, webhooks, scraping
Data quality layers — schema validation, null checks, deduplication, anomaly detection
Transformation — dbt, Pandas, Polars for large-scale processing
Data lake setup — S3 + Parquet + Athena for serverless querying
Vector data pipelines — embedding generation, upsert to vector DB, nightly refresh
Third-party API integrations — any service with a public API, with proper error handling, rate limit management, and retry logic
Bi-directional sync — keep two systems in sync with conflict resolution
Webhook ingestion — receive, validate, deduplicate, and process incoming events
SDK generation for your own API — auto-generated clients in Python, Go, TypeScript
Technology stack
KinesisS3AthenaDelivery
Documented pipelines, data quality dashboard, monitoring alerts, and a runbook.
Next step
Need this service scoped for your project?
We can map the implementation, estimate the work, and show where the technical risk sits before you commit.