Senior Data Engineer — Billing Data Migration
Gardner Resources Consulting, LLC
We are looking for a Senior Data Engineer to support a major billing data migration from Recurly to Stripe . This engineer will play a key role in building and validating the data infrastructure required to move from the existing Recurly environment to Stripe, including ingestion into BigQuery, data transformation, modeling, reconciliation, and downstream reporting.
The ideal candidate is a hands-on Data Engineer who is strong in SQL and Python and has experience building production data pipelines and data models in a modern cloud data stack. Experience working with financial, billing, subscription, or revenue data is particularly valuable.
Project
- Ingestion — stand up Stripe data ingestion into BigQuery
- Model rebuild — port billing, subscription, and revenue models from Recurly-based sources to Stripe in SQLMesh
- Reconciliation — parallel-run validation between Recurly and Stripe outputs, with Finance-ready reconciliation reporting
- Downstream cutover — repoint dashboards and downstream consumers; deprecate Recurly pipelines
Must Haves:
- 7+ years of professional Data Engineering experience.
- Strong SQL skills, including complex queries, transformations, data validation, and analytical problem solving.
- Strong Python experience.
- Experience working with modern cloud data warehouses, preferably GCP and BigQuery .
- Experience designing and maintaining production-grade ETL/ELT pipelines.
- Strong understanding of data modeling and data architecture.
- Experience with data orchestration tools such as Dagster, Airflow, or similar.
- Experience with transformation frameworks such as SQLMesh, dbt, or similar.
- Experience with data ingestion tools such as Fivetran or similar.
- Experience working with financial, billing, subscription, payments, or revenue data is highly preferred.
- Experience performing data migrations, system migrations, or parallel-system validation is a strong plus.
- Experience with Git/GitHub and CI/CD workflows.
- Strong problem-solving and troubleshooting skills.
- Ability to communicate effectively with both engineering and business stakeholders
Technical Environment
- GCP/BigQuery
- SQL/SQLMESH
- Python
- Fivetran
- Git/GitHub
- CI/CD
- Data lineage and governance tooling
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