I will build AWS data pipelines and etl with python, airflow and dbt

Data pipelines are easy to build and hard to keep running. I build the kind that survive schema changes, late files and Monday mornings.

I am a Lead Data and AI Engineer with 9 plus years of experience. I have built data platforms at Amazon, Delivery Hero, Goldman Sachs and Orion, and I hold 13 cloud certifications including AWS Data Engineer Associate and AWS Solutions Architect.

WHAT I BUILD FOR YOU

Ingestion from APIs, databases, S3, SaaS tools and event streams

Orchestration in Airflow, Dagster or AWS Step Functions

Transformations as dbt models with tests and documentation

Incremental loads, backfills and reruns that are safe to repeat

Data quality checks and alerts, so failures reach you and not your customers

Infrastructure as code in Terraform, with CI/CD

STACK

Python, SQL, Airflow, dbt, AWS Glue, Spark, Kafka, Snowflake, Redshift, BigQuery, Terraform

WHAT YOU GET

Documented code in your own repository, a runbook and a handover call.

Tell me your sources, your volumes and how fresh the data has to be, and I will tell you honestly what it takes.