AIML Data Engineer: Build Pipelines & Insights

Socket.dev; Austin (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

Socket.dev is seeking an AIML Data Engineer to own end-to-end data pipelines and telemetry infrastructure supporting AI/ML initiatives in a fast-paced environment. You will transform raw data from conversations into model-ready formats, orchestrate scoring workflows, and partner with program managers to turn data into actionable insights for leadership.

The role blends full-stack data engineering and analytics, requiring strong SQL/Python skills, cloud platform experience, and a track record of

Qualifications

• Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or related field (or equivalent experience)
• 4+ years of experience in data engineering or analytics engineering
• Strong proficiency in SQL and Python for both data engineering and analytical investigation
• Experience with cloud data platforms (Snowflake, Databricks, or similar)
• Experience with ETL/ELT tools and pipeline orchestration (dbt, Airflow, Prefect, or similar)
• Demonstrated ability to conduct root cause analysis and translate data findings into actionable recommendations
• Experience with version control (Git) and CI/CD practices

Responsibilities

• Design and maintain data pipelines to ingest and transform support conversation data
• Develop feature engineering and telemetry infrastructure for AIML initiatives
• Collaborate with program managers to investigate trends and surface actionable insights
• Provide data-driven deep dives and storytelling to leadership and stakeholders

Skills

SQL

Python

Root cause analysis

Git & CI/CD

Data engineering

Education

Bachelor's degree in CS/Data Science/Engineering

Tools

Snowflake

Databricks

dbt

Airflow

Prefect

Tableau

Streamlit

Job description

Socket.dev is seeking an AIML Data Engineer to own end-to-end data pipelines and telemetry infrastructure supporting AI/ML initiatives in a fast-paced environment. You will transform raw data from conversations into model-ready formats, orchestrate scoring workflows, and partner with program managers to turn data into actionable insights for leadership.

The role blends full-stack data engineering and analytics, requiring strong SQL/Python skills, cloud platform experience, and a track record of