Data Pipeline Development: ETL, ELT & Streaming by Tran Tien VanData Pipeline Development: ETL, ELT & Streaming by Tran Tien Van
Data Pipeline Development: ETL, ELT & StreamingTran Tien Van
Dashboards go stale, scripts break at night and nobody trusts the numbers. I build production ETL, ELT and streaming pipelines that land clean, validated data in your warehouse and alert you before anything goes wrong.
What you get
Pipelines in Airflow, dbt, Kafka, Dagster or AWS Glue
Source contracts, freshness checks, validation and SLA alerts
Replay paths plus audit and lineage tables
Delivery into BigQuery, Snowflake, Athena, PostgreSQL or SQL Server
Runbooks and handover, so your team owns the pipeline
Proof
Healthcare claims pipeline: Airflow and AWS Glue land member, claims and provider files (CSV, TSV, fixed-width, Excel) into Amazon Athena with full audit and lineage (built for a client)
Vendor intelligence on GCP: scoring across 81 vendor sources stored in BigQuery, about 7.6K accounts processed (built for a client)
My own open-source project: a stock price pipeline on Azure with Airflow and Docker, daily LSTM forecasts on Databricks, reported in Power BI
Van Data Team pipelines hold 99%+ uptime in the first 90 days after launch
Timeline: 2 to 6 weeks from kickoff to production.
Dashboards go stale, scripts break at night and nobody trusts the numbers. I build production ETL, ELT and streaming pipelines that land clean, validated data in your warehouse and alert you before anything goes wrong.
What you get
Pipelines in Airflow, dbt, Kafka, Dagster or AWS Glue
Source contracts, freshness checks, validation and SLA alerts
Replay paths plus audit and lineage tables
Delivery into BigQuery, Snowflake, Athena, PostgreSQL or SQL Server
Runbooks and handover, so your team owns the pipeline
Proof
Healthcare claims pipeline: Airflow and AWS Glue land member, claims and provider files (CSV, TSV, fixed-width, Excel) into Amazon Athena with full audit and lineage (built for a client)
Vendor intelligence on GCP: scoring across 81 vendor sources stored in BigQuery, about 7.6K accounts processed (built for a client)
My own open-source project: a stock price pipeline on Azure with Airflow and Docker, daily LSTM forecasts on Databricks, reported in Power BI
Van Data Team pipelines hold 99%+ uptime in the first 90 days after launch
Timeline: 2 to 6 weeks from kickoff to production.