Senior Data Engineer — Build Scalable Pipelines & Snowflake

Hood L2; New York (NY); À distance; USD 120 000 - 160 000; Plein temps

Avantages offerts par ce poste

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 0

Résumé du poste

Alchemy is building the data platform that powers product usage and revenue insights. You will own ingestion, schema changes, and checks to ensure datasets are current and correct, collaborating with analytics engineers and data scientists.

As a Data Engineer, you'll build batch and streaming pipelines connecting operational databases, product events, billing, and external sources, while optimizing Snowflake, orchestration with Airflow/dbt, and data quality checks.

Qualifications

• Experience independently 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 data warehouse and with performance tuning and access management.
• Experience with orchestration and transformation tools such as Airflow and dbt.
• Understanding of data modeling, incremental processing, schema evolution, and data-quality testing.
• Ability to trace data discrepancies from downstream reports to source and fix root causes.
• Ability to translate stakeholder requests into reusable datasets or tooling.

Responsabilités

• Build batch and streaming pipelines that connect operational databases, product events, billing systems, and external sources to the internal data platform.
• Ensure ingestion recoverability via change-data capture, schema changes, idempotent processing, and safe backfills.
• Operate and improve Snowflake, including access controls, workload management, and cost optimization.
• Improve orchestration and deployment workflows so engineers can test, ship, and debug pipelines safely.
• Build data-quality checks to detect stale, missing, duplicated, or inconsistent records before downstream use.
• Collaborate with analytics partners on shared data models, source definitions, and documentation; clarify ownership and dependencies.
• Reduce recurring manual work by building reusable self-serve data tools.
• Participate in production support and incident response for pipelines and the data platform.

Connaissances

SQL

Python

Data modeling

Data quality

Outils

Snowflake

Airflow

dbt

Apache Iceberg

Spark

Trino

Description du poste

Alchemy is building the data platform that powers product usage and revenue insights. You will own ingestion, schema changes, and checks to ensure datasets are current and correct, collaborating with analytics engineers and data scientists.

As a Data Engineer, you'll build batch and streaming pipelines connecting operational databases, product events, billing, and external sources, while optimizing Snowflake, orchestration with Airflow/dbt, and data quality checks.