Senior Data Engineer: Build Scalable Pipelines

Alchemy Health; New York (NY); On-site; USD 160,000 - 175,000; Full time

Benefits offered by this job

Private Health Insurance

Gym Reimbursement

Commuter Benefits

Flexible Time Off

In-Office Group Meals

Learning & Development Stipend

Company Sponsored Conferences & Events

Books & Audiobook subscription with 1B

Job summary

Alchemy is seeking a Data Engineer to build and operate the internal data platform that powers product usage, revenue, and cost insights. You will own ingestion, schema changes, and checks, collaborating with analytics engineers and data scientists to define datasets for reporting, analysis, and AI-assisted tools.

You will work with Snowflake, Airflow, and dbt to deliver reliable pipelines, implement data-quality checks, and enable self-service datasets for downstream teams.

Qualifications

• Experience building and operating production data pipelines and the infrastructure around them.
• Strong SQL and Python skills, including testing, debugging, and maintainable software design.
• Experience with Snowflake or a comparable warehouse, including performance tuning and access management.
• Experience with workflow orchestration and transformation tools such as Airflow and dbt, or equivalent systems.
• Understanding of data modeling, incremental processing, schema evolution, and data-quality testing; able to trace discrepancies to source and fix root causes.
• Good judgment about stakeholder needs: deliver reusable datasets or tooling and communicate trade-offs clearly.

Responsibilities

• Build batch and streaming pipelines connecting databases, product events, billing, and external sources.
• Make ingestion recoverable with CDC, schema changes, idempotent processing, and safe backfills.
• Operate and optimize Snowflake, including access controls, WM, and cost management.
• Improve orchestration and deployment workflows for safe testing, shipping, and debugging.
• Create data-quality checks to detect stale, missing, duplicated, or inconsistent records.
• Collaborate with analytics partners on data models, source definitions, and documentation.
• Define dataset ownership and upstream dependencies; reduce manual work with reusable tools.
• Participate in production support and incident response for pipelines and the data platform.

Skills

SQL

Python

Data modeling

Incremental processing

Schema evolution

Data quality testing

Stakeholder engagement

KPI reporting

Kafka

Spark

Iceberg

Trino

Tools

Airflow

dbt

Snowflake

Job description

Alchemy is seeking a Data Engineer to build and operate the internal data platform that powers product usage, revenue, and cost insights. You will own ingestion, schema changes, and checks, collaborating with analytics engineers and data scientists to define datasets for reporting, analysis, and AI-assisted tools.

You will work with Snowflake, Airflow, and dbt to deliver reliable pipelines, implement data-quality checks, and enable self-service datasets for downstream teams.