Senior Data Engineer: Build Scalable Data Pipelines & Platform

Alchemy; United States; Remote; USD 120,000 - 170,000; Full time

Job summary

Alchemy is seeking a Data Engineer to build and operate the internal data platform that helps understand product usage, revenue, and the cost of serving customers. You will own ingestion, schema changes, and checks for shared datasets.

Collaborate with analytics engineers and data scientists to define datasets for reporting, analysis, and AI-assisted tools. Build pipelines, ensure data quality, and optimize Snowflake and workflows.

Qualifications

• Experience independently building and operating production data pipelines.

Responsibilities

• Build batch and streaming pipelines connecting databases, product events, billing systems and external sources to the internal data platform.
• Make ingestion recoverable through change-data capture, schema-change handling, idempotent processing, and safe backfills.
• Operate Snowflake, including access controls, workload management, query performance and compute and storage costs.
• Improve orchestration and deployment workflows so engineers can test, ship, and debug pipelines safely.
• Build data-quality checks that detect stale, missing, duplicated, or inconsistent records before they reach downstream consumers.
• Work with analytics partners on shared data models, source definitions, and documentation.
• Make dataset ownership and upstream dependencies clear.
• Reduce recurring manual work and build reusable tools for self-service data access.
• Participate in production support and incident response for pipelines and the data platform.
• Restore data flow, reconcile affected datasets, and fix the causes of recurring failures.

Skills

SQL

Python

Airflow

dbt

Snowflake

Data modeling

Data quality testing

Incident response

Tools

Snowflake

Airflow

dbt

Job description

Alchemy is seeking a Data Engineer to build and operate the internal data platform that helps understand product usage, revenue, and the cost of serving customers. You will own ingestion, schema changes, and checks for shared datasets.

Collaborate with analytics engineers and data scientists to define datasets for reporting, analysis, and AI-assisted tools. Build pipelines, ensure data quality, and optimize Snowflake and workflows.