Analytics Engineer
Analytics Engineers at AI infrastructure companies shape how their organizations reason about product performance, infrastructure efficiency, and customer value through clean, well-documented data models and metrics layers. They spend their days writing SQL and dbt to transform raw events from AI platforms—GPU utilization, inference costs, model performance, billing data—into trusted datasets that power dashboards, experiments, and strategic decisions. What sets this role apart from pure data engineering is the focus on business metrics and stakeholder enablement; these engineers are equally comfortable explaining revenue recognition logic to Finance teams as they are optimizing query costs or designing dimensional schemas. They typically report into data or analytics leadership and partner closely with Product, GTM, and Engineering to translate ambiguous questions into scalable data infrastructure that lets non-technical users self-serve insights.
Skills
What companies are looking for in this role.
Designing and implementing scalable data pipelines and ETL workflows
Writing and optimizing SQL queries for data extraction and transformation
Building and maintaining data models and dimensional schemas
Defining and operationalizing business metrics and KPIs
Creating dashboards and data visualizations for business stakeholders
Ensuring data quality, integrity, and validation across pipelines
Translating business requirements into technical data solutions
Programming in Python for data manipulation and automation
Integrating and orchestrating data from multiple heterogeneous sources
Building self-serve analytics and data products for business users
Managing version control and collaborating on codebases
Debugging and troubleshooting complex data pipeline issues
Building internal data infrastructure and platforms for organizational scale
Designing data schemas and event taxonomy for product instrumentation
Designing and implementing automated data quality monitoring and anomaly detection
Optimizing data warehouse costs and query performance
Creating and maintaining data lineage and documentation
Building AI-powered data systems and semantic layers for machine learning use cases
Implementing data governance frameworks and documentation standards
Developing autonomous agents that conduct end-to-end data analysis and insights generation
Partnering with cross-functional stakeholders to identify and solve data problems
Communicating complex data insights to technical and non-technical audiences
Leading analytics projects from conception through implementation and production
Establishing best practices and mentoring teams on analytics engineering standards
Balancing technical quality with speed and pragmatism in fast-moving organizations
Technology
The tools and technologies that define this role.
Open Jobs
22 open Analytics Engineer jobs across 17 companies.
Other Data & Analytics roles
Applies statistical modeling, machine learning, and experimentation to extract insights from data.
Builds and maintains data pipelines, warehouses, and infrastructure that enable analytics and ML.
Analyzes data to generate actionable business insights, builds dashboards and reports.
Data professionals specializing in marketing and go-to-market measurement, attribution modeling, and revenue intelligence. Focuses on building analytical frameworks, experimentation, and data-driven insights to optimize GTM strategy. The emphasis is on analytics methodology and data infrastructure for marketing.
Manages data labeling, annotation, and curation operations for machine learning.