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Data Engineer to help build data platform

Budżet: - HOURLY / FULL_TIME ⭐ 5.00 (42) Hong Kong

apache-airflow-platform, etl-pipelines, python, github

About the Role We're looking for a Senior Data Engineer to build our data platform from scratch, a rare greenfield opportunity to make the foundational architecture calls yourself. You'll design the pipelines that bring together high-volume payment transactions, marketing analytics, and operational data across AWS and GCP into a unified Lakehouse. This is a hands-on, ownership-heavy role. What You'll Do Design and build ingestion pipelines for high-volume payment data (Stripe, PayPal, Solidgate), marketing analytics (GA4, GTM, Google Ads, Amplitude), and operational databases (MongoDB, PostgreSQL). Build the data infrastructure for a Lakehouse using AWS and GCP. Build medallion-layer transformation models (Bronze → Silver → Gold) in dbt or SQLMesh, with payments on Redshift and marketing on BigQuery. Own orchestration end-to-end in Dagster or Airflow, lineage, sensors, backfills, retries, and alerting across the full asset graph. Implement infrastructure as code best practices, cost controls etc. What We're Looking For 3+ years building production data platforms and pipelines from the ground up. Deep expertise in Dagster or Airflow, including lineage, backfill, and retry strategies. Hands-on experience with dbt or SQLMesh, version-controlled transformations. Strong AWS and GCP skills, with Terraform for infrastructure as code and a cost-conscious (FinOps) approach. Strong written communication and the ability to work autonomously in a remote, async environment. Nice to Have Familiarity with data mesh principles, domain ownership, or data product design. Experience with Apache Spark or Flink for large-scale compaction workloads.
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