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Remote mid-senior data role with a popular title but niche Snowflake/dbt stack yields moderate competition.
Specialized data-platform stack (Snowflake, dbt, Dagster, PySpark) makes cross-industry transferability medium.
Explicit 6-8 year requirement plus mandatory Snowflake, dbt, Dagster and PySpark skills create high filter strictness.
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Design, develop, and maintain orchestrated data pipelines using Dagster, Python, and PySpark for scalable, reliable data platforms.
Build modular transformation models with dbt and optimize Snowflake data models, SQL queries, and warehouse workloads.
Implement data-quality checks, data lineage, observability, failure-handling, and integrate data sources via APIs including GraphQL where needed.
3+ years of data engineering experience with cloud data platforms.
Strong hands-on experience with Snowflake, Dagster, and dbt.
Advanced Python, SQL, and PySpark programming skills for production-grade data pipelines.
Work Experience Required: 6-8 years (explicitly mentioned in the JD)
Experienced in building and optimizing tested, maintainable data workflows in cloud environments with a disciplined engineering approach.
Comfortable collaborating across analytics, product, and engineering teams to translate business requirements into data solutions.
Familiar with data governance, lineage, observability, and integration of GraphQL APIs for data consumption.