Senior Data Engineer New York San Francisco

Alchemy

New York (NY)

On-site

USD 120,000 - 160,000

Full time

2 days ago

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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 B‑

Job summary

Alchemy is seeking a Data Engineer to build and run the internal data platform that powers understanding of product usage, revenue, and serving costs. You will own ingestion, schema changes, and data quality checks while collaborating with analytics engineers and data scientists to define datasets for reporting and AI tools.

You will work with analytics partners on shared data models, ownership, and upstream dependencies, striving for reusable, self-service data capabilities and robust

Qualifications

Experience building and operating production data pipelines and the infrastructure around them.
Strong SQL and Python skills, including testing and debugging.
Experience with Snowflake or a comparable warehouse and with access management.
Experience with workflow orchestration and transformation tools (Airflow, dbt).
Understanding of data modeling, incremental processing, and data-quality testing.
The ability to trace data discrepancies from downstream reports to their sources and fix them.
Good judgment turning recurring requests into reusable datasets or tooling.

Responsibilities

Build batch and streaming pipelines connecting databases, product events, billing, and external sources.
Make ingestion recoverable via change-data-capture, schema-change handling, idempotent processing.
Operate and improve Snowflake, including access controls and cost management.
Improve orchestration and deployment workflows for safe testing and shipping.
Build data-quality checks to detect stale, missing, or inconsistent records.
Collaborate with analytics partners on data models, definitions, and ownership.
Reduce manual work by building reusable self-service data tools.
Participate in production support and incident response for pipelines.

Skills

SQL

Python

Data pipelines

Data quality

Troubleshooting

Tools

Snowflake

Airflow

dbt

Kafka

Apache Iceberg

Spark

Trino

Job description

About Alchemy

Alchemy is the Web3 infrastructure and developer platform that powers millions of users and the world’s most innovative blockchain applications. From enabling $1+ trillion in financial transactions worldwide to scaling L2s and enabling DeFi, Alchemy provides the infrastructure and tools developers need to build reliable, scalable, and accessible experiences.

visit alchemy.com.

The Role

Build and run the internal data platform that helps Alchemy understand product usage, revenue, and the cost of serving customers. The existing Data Engineer intake centers on ingestion, Snowflake operations, workflow orchestration, data quality, and collaboration with analytics partners.

You will own ingestion, schema changes, and checks that show whether shared datasets are current and correct. You will work with analytics engineers and data scientists to define those datasets for reporting, analysis, and AI-assisted tools.

What You Will Do

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.

What We Are Looking For

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.

Blockchain experience is not required.

Helpful Experience

Kafka, database replication, or change-data-capture systems.
Apache Iceberg, Spark, Trino, or other lakehouse and query technologies.
Infrastructure as code, data observability, lineage, and disaster recovery.
Usage metering, billing and revenue data, or semantic layers for self-service analytics.

What Success Looks Like

Within three months:

You own a production pipeline and have shipped an improvement to its freshness, reliability, or operating cost.
Downstream users can see whether its data is current, recovery procedures have been tested, and a recurring manual request has become a reusable dataset or tool.

Benefits & Perks