Analytics Data Engineer: Metrics, Models & Dashboards

EngineersOfAI; San Francisco (CA); On-site; USD 180,000 - 200,000; Full time

Job summary

EngineersOfAI, based in San Francisco, seeks an experienced Data Engineer, Analytics to own curated data assets, metrics, and dashboards that data scientists, product managers, and business stakeholders can trust and self-serve from.

You will partner with data science, product, and engineering to translate business questions into well-modeled, performant datasets and to surface metrics in visualization tools. Build executive dashboards and enforce data quality standards across the organization.

Qualifications

• 3+ years of analytics or data engineering with a focus on curated datasets.
• 3+ years designing, developing, and maintaining robust data models across sources.
• 3+ years writing accurate SQL code.
• Experience powering metrics and dashboards for stakeholders.
• Fluency in Python with version control/CI/CD fundamentals.
• Experience building executive-level dashboards using BI tools.
• Strong business acumen and ability to translate questions into data models.
• Excellent communication bridging technical and business teams.

Responsibilities

• Design, build, and maintain curated analytical datasets and data models for metrics and dashboards.
• Own metric definitions end to end from modeling to production surfaces.
• Build and maintain executive dashboards and self-serve reporting for stakeholders.
• Partner with data science, product, and engineering to translate business questions into data assets.
• Establish data quality standards with testing, documentation, and monitoring.
• Drive adoption of consistent data modeling patterns and documentation.

Skills

Analytics

Data Modeling

SQL

Python

BI Tools

Data Pipelines

Tools

dbt

BigQuery

Looker

Tableau

Job description

EngineersOfAI, based in San Francisco, seeks an experienced Data Engineer, Analytics to own curated data assets, metrics, and dashboards that data scientists, product managers, and business stakeholders can trust and self-serve from.

You will partner with data science, product, and engineering to translate business questions into well-modeled, performant datasets and to surface metrics in visualization tools. Build executive dashboards and enforce data quality standards across the organization.