Data Engineer
About the role
Arena Intelligence is seeking an experienced Data Engineer to own the data foundations that power real-world AI evaluation. This role involves designing and building analytics-layer data models, pipelines, and metrics that turn raw user activity and votes into trusted insights for the public, AI labs, and enterprise customers. You'll work closely with researchers, product managers, and engineers to define schemas, standardize metrics, and ensure that our evaluation data is accurate, interpretable, and scalable.
This role sits at the intersection of data engineering, analytics, and product. Your work will directly shape how AI performance is measured, understood, and acted upon across the industry. Ideal for someone who enjoys building clean, well-modeled data systems, cares deeply about data quality and correctness, and wants to see their work influence both product decisions and external customers.
Responsibilities
Own the design and implementation of analytics-ready data models, schemas, and tables in our data warehouse
Build and maintain reliable data pipelines (batch and incremental) that transform raw event and vote data into standardized, trusted datasets
Define and standardize core metrics used across product, research, and customer-facing evaluations
Partner with product managers and researchers to translate evaluation questions into robust data models
Develop and maintain dashboards, reports, and data artifacts used by internal teams and external partners
Ensure data quality through testing, validation, monitoring, and documentation
Optimize queries and pipelines to support large-scale analytical workloads
Contribute to improving data discoverability, lineage, and documentation across the warehouse
Requirements
3+ years of experience in analytics engineering, data engineering, or a closely related role
Strong proficiency in SQL, with experience designing analytics-friendly schemas and transformations
Hands-on experience working with a modern data warehouse (e.g., Databricks, Snowflake, BigQuery)
Experience building and orchestrating data pipelines using Airflow or similar workflow orchestration tools
Proficiency in Python for data transformation, validation, and pipeline development
A strong understanding of data modeling best practices (e.g., dimensional modeling, metrics layers)
Experience operating and debugging production data pipelines with a focus on correctness and reliability
Qualifications
Experience with Spark or other distributed data processing frameworks
Familiarity with Delta Lake or similar table formats
Experience supporting experimentation, evaluation, or metrics-heavy products
Exposure to machine learning systems or ML-adjacent analytics
Experience improving data discovery, lineage, or documentation at scale
Skills
SQL
Data modeling best practices
Data pipeline development
Python
Spark or similar distributed data processing frameworks
Delta Lake or similar table formats
Machine learning systems or ML-adjacent analytics
Data discovery, lineage, or documentation
Benefits
We offer competitive compensation and equity aligned to the markets where our team members are based. The base salary range will depend on the candidate’s permanent work location. Comprehensive health and wellness benefits, including medical, dental, vision, and additional support programs. The opportunity to work on cutting-edge AI with a small, mission-driven team. A culture that values transparency, trust, and community impact.
Pay
$150K - $350K
Schedule
N/A