Data Science Director — AI/ML Data Architect (Hybrid)

EY-Parthenon; Seattle (WA); Hybrid; USD 205,000 - 235,000; Full time

Benefits offered by this job

Hybrid work model

Competitive compensation

Job summary

EY-Parthenon seeks a Growth Platforms Data Scientist Director in Seattle to architect and scale multi-source data pipelines powering AI/ML-driven agents and dashboards. You will transform data, ensure quality, and collaborate with business leaders to solve high-impact questions with data.

The role requires fluency in SQL/Python/Scala, experience with cloud data stacks (GCP/AWS, Snowflake, BigQuery, Databricks), and expertise in ETL, data provenance, and governance.

Qualifications

• Bachelor’s degree in Business, Statistics, Economics, Mathematics, Engineering, Computer Science, Analytics, or related field plus 5 years of experience; or a graduate degree with ~3 years of experience.
• Experience in data engineering or hybrid data science roles focused on pipeline scalability and schema management.
• Expertise in cloud-native data infrastructure (GCP/AWS, Snowflake, BigQuery, Databricks, Delta Lake).
• Strong SQL/Python/Scala and orchestration tools (Airflow, dbt).

Responsibilities

• Build and scale multi-source data pipelines powering client engagements.
• Architect, clean, transform, and enrich data for AI/ML-driven agents and dashboards.
• Collaborate with business leaders and C-level executives to solve critical questions with data.

Skills

SQL

Python/Scala

ETL design

Data pipelines

Data governance

Cloud platforms

Education

Bachelor's degree in related field

Graduate degree (MS/PhD) in related field

Tools

Airflow

dbt

Snowflake

BigQuery

Databricks

Delta Lake

Job description

EY-Parthenon seeks a Growth Platforms Data Scientist Director in Seattle to architect and scale multi-source data pipelines powering AI/ML-driven agents and dashboards. You will transform data, ensure quality, and collaborate with business leaders to solve high-impact questions with data.

The role requires fluency in SQL/Python/Scala, experience with cloud data stacks (GCP/AWS, Snowflake, BigQuery, Databricks), and expertise in ETL, data provenance, and governance.