This role pays more than
50%
of similar roles. Most pay
$149,500–$231,187
— the shaded band above.
At the midpoint, this role pays about
$196k
versus about
$190k
for comparable roles.
Based on 240 similar postings.
Employer
About Coinbase
Coinbase Global is a publicly traded cryptocurrency exchange platform where consumers can buy, sell, and store digital currencies including Bitcoin, Ethereum, and hundreds of other cryptocurrencies. Industry: Cryptocurrency Exchange & Financial Technology
Coinbase currently has
58 open roles
on FindRole.
Listed pay typically runs
$215,177–$253,150
across 50 roles with salary data.
As a Senior Analytics Engineer on the GFCO Analytics Engineering team within the Customer Experience organization, you will build data foundations and analytical models that power customer experience and compliance operations. You will own end-to-end data models, design experiments, and develop production pipelines for ML-powered analytics products like LLM-based contact classification and friction detection. Your daily work involves creating self-service dashboards, executing causal inference frameworks such as A/B tests and propensity score matching, and performing deep-dive investigations using Bayesian reasoning and time series analysis. You will utilize SQL, Python, dbt, Airflow, Snowflake, Looker, Tableau, and Hex to solve problems in the compliance and regulatory data domains, including AML and transaction monitoring. The role focuses on improving customer outcomes, operational efficiency, and compliance posture through scalable data solutions and rigorous statistical methods.
Build and maintain production data pipelines, dimensional models, and ML-powered analytics products for customer experience and compliance.
Develop self-service dashboards and AI-assisted tools in Looker, Hex, or Python to reduce time-to-insight for stakeholders.
Design and execute causal inference frameworks and quasi-experiments like A/B tests to measure the impact of CX programs.
Translate business requirements into scalable data solutions while managing a long-term analytics roadmap.
Conduct deep-dive investigations using advanced statistical methods like Bayesian reasoning and time series analysis to identify operational improvements.
Establish analytics engineering standards, documentation practices, and testing frameworks to ensure high data quality and rigor.
What we're looking for
At least 5 years of experience in analytics engineering, data science, or data engineering.
Experience with production data pipelines, dimensional models (star/snowflake), and statistical or ML models using dbt, Airflow, or Snowflake.
Advanced proficiency in SQL and Python for data modeling, pipeline orchestration, and machine learning deployment.
Demonstrated experience designing and executing A/B tests, quasi-experiments, and causal inference methods like difference-in-differences and propensity score matching.
Proven success building production-grade dashboards and self-serve analytics solutions in tools like Looker, Tableau, or Hex.
Experience applying ML techniques to operational problems including classification, detection, and attribution pipelines.
Familiarity with compliance or regulatory data domains such as AML, transaction monitoring, and case handling.
Ability to use generative AI responsibly to deliver business-ready outputs and improve workflow efficiency.
SQL
dbt
Star Schema
GCP
AWS
Azure
Data Governance
Semantic Layer
AI Tools
Data Transformation
Data Quality
Monitoring and Alerting
Source-to-Target Mapping