Senior Data Platform Engineer – Pipelines & Snowflake

Alchemy; New York (NY); On-site; USD 120,000 - 170,000; 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 building the internal data platform to understand product usage, revenue, and cost of serving customers. You will own ingestion, schema changes, and checks for shared datasets, collaborating with analytics engineers and data scientists to define datasets for reporting and AI tools.

You will lead batch and streaming pipelines across databases, events, billing, and external sources, and improve orchestration, data quality, and data accessibility across the organization.

Qualifications

• Experience independently 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.
• The ability to trace a data discrepancy from a downstream report back to its source, explain the cause, and fix it.
• Good judgment about stakeholder needs: turn recurring requests into reusable datasets or tooling, and make trade-offs clear.

Responsibilities

• Build batch and streaming pipelines that connect operational 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 and improve 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

Data modeling

Strong debugging

Incremental processing

Tools

Snowflake

Airflow

dbt

Kafka

Iceberg

Job description

Alchemy is building the internal data platform to understand product usage, revenue, and cost of serving customers. You will own ingestion, schema changes, and checks for shared datasets, collaborating with analytics engineers and data scientists to define datasets for reporting and AI tools.

You will lead batch and streaming pipelines across databases, events, billing, and external sources, and improve orchestration, data quality, and data accessibility across the organization.