We need a data engineer to build and maintain the pipelines that keep our analytics and product data trustworthy. You'll design schemas, own transformation logic in dbt, and make sure the data platform scales as more teams depend on it. Someone who cares about data quality as much as pipeline uptime will thrive here, since a pipeline that runs on time but produces wrong numbers is arguably worse than one that just fails loudly.
What you'll do
- Design and maintain ETL/ELT pipelines feeding the data warehouse
- Build and own transformation models using dbt with clear testing
- Optimize query performance across large tables in Snowflake or BigQuery
- Monitor pipeline health and resolve data quality issues proactively
- Partner with analysts and data scientists on data model design
- Document data lineage and schema changes for downstream consumers
What we're looking for
- 4+ years in data engineering or a related backend engineering role
- Strong SQL skills and hands-on experience with dbt
- Experience with a cloud data warehouse such as Snowflake or BigQuery
- Proficiency in Python for pipeline orchestration and scripting
- Familiarity with workflow orchestration tools like Airflow
- Attention to data quality and willingness to write robust tests
Nice to have
- Experience with streaming data pipelines using Kafka
- Background supporting machine learning feature pipelines
- Familiarity with infrastructure-as-code for data infrastructure
About Meridian West
About Meridian West: Meridian West provides payment and treasury infrastructure trusted by enterprise finance teams to move money reliably at scale. Headquartered in New York, the company combines regulatory, risk, and engineering expertise to support clients processing billions of dollars in annual volume across marketplaces, payroll, and insurance.
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