Senior ML Data Infrastructure Engineer (GCP) — Remote

Apex Systems; Sunnyvale, Northern (CA, KY); Hybrid; USD 103,000 - 117,000; Full time

Benefits offered by this job

Health insurance

401K

ESPP

HSA

Job summary

Everforth Apex Systems is seeking a seasoned ML/Data Engineer to build and scale our ML data infrastructure platform in Sunnyvale. You will design data pipelines, feature stores, and tooling that support data scientists and production inference pipelines.

You will work with Python, SQL, Spark, and GCP services to implement robust data processing, dataset versioning, and reproducibility, while aligning with security and governance practices. Remote-friendly with strong collaboration across teams.

Qualifications

• 7+ years in software engineering with 3+ years in data infrastructure.
• Proficient in Python and SQL with cloud data tooling.
• Experience with data quality monitoring and testing frameworks.
• Experience with Spark-based data processing.
• Knowledge of feature stores (Feast, Tecton) and data versioning.
• Familiarity with Airflow and Dagster for orchestration.

Responsibilities

• Design scalable data pipelines for ML training and validation.
• Build and maintain feature stores for batch and real-time features.
• Develop data quality monitoring, validation, and testing.
• Create dataset versioning, lineage tracking, and reproducibility systems.
• Implement data documentation and discovery tools.
• Collaborate with data scientists to optimize data prep workflows.

Skills

Python

SQL

GCP Dataflow

Vertex AI Feature Store

Dataproc

Spark

Airflow

Dagster

Data quality tests

Tools

Feast

Tecton

dbt

Job description

Everforth Apex Systems is seeking a seasoned ML/Data Engineer to build and scale our ML data infrastructure platform in Sunnyvale. You will design data pipelines, feature stores, and tooling that support data scientists and production inference pipelines.

You will work with Python, SQL, Spark, and GCP services to implement robust data processing, dataset versioning, and reproducibility, while aligning with security and governance practices. Remote-friendly with strong collaboration across teams.