Senior Analytics Engineer (Data Modeling & BI)

feverup; United States; Hybrid; USD 110,000 - 170,000; Full time

Benefits offered by this job

Home-office setup

Health insurance

Stock options

Performance bonus

English lessons

Gym membership

Job summary

feverup is seeking a Senior Analytics Engineer to bridge data engineering and business analytics, translating needs across marketing, CRM, product, and B2B into reusable models and reporting assets.

You will build SQL-based models, define metrics like revenue and engagement, partner with data engineers, and improve data quality, governance, and observability while enabling self-service analyses with BI tools.

Qualifications

• Strong SQL and data modeling skills (star/snowflake/data vault).
• Experience with dbt or equivalent transformation framework.
• Hands-on Python and orchestration tools (Airflow, Dagster, Prefect).
• Familiarity with cloud data warehouses and BI tools.
• Understanding of data quality, governance, and observability practices.
• Fluent in Spanish and English for collaboration.

Responsibilities

• Create and maintain SQL-based data models for reporting and self-service.
• Partner with data engineers to define business measures (revenue, engagement, marketing, B2B).
• Develop reusable data assets addressing business questions.
• Improve data quality, testing, observability, and governance with engineering partners.
• Help stakeholders use BI tools and develop custom reporting.
• Contribute to Python-based orchestration pipelines in a federated data approach.
• Use AI coding assistants to support development work.

Skills

SQL

Data modeling (star/snowflake/data‑hub

dbt

Python

Orchestration tools (Airflow, Dagster,

Cloud data warehouses

Data quality & governance

Spanish & English proficiency

Education

Degree in computer data/engineering or related field

Tools

dbt

Airflow

Dagster

Prefect

Snowflake

Job description

Role overview

Build trusted, well-structured data products that help business teams make decisions and explore information independently. This senior analytics engineering role connects data engineering with business analytics: you’ll translate needs across areas such as marketing, customer relationship management, product, and B2B into reusable models, agreed metrics, and useful reporting assets.

Responsibilities

• Create and maintain SQL-based data models that turn raw inputs into reliable datasets for reporting and self-service analysis.
• Partner with data engineers to define and certify important business measures, including revenue, engagement, marketing performance, and B2B indicators.
• Work with business teams to understand questions and develop reusable data assets that address them.
• Improve data quality, consistency, testing, observability, and governance in collaboration with engineering partners.
• Help stakeholders use BI and visualization tools effectively, and develop custom reporting where needed.
• Contribute to Python-based orchestration pipelines and domain-owned datasets within a federated data approach.
• Use AI coding assistants and related tools to support day-to-day development work.

Requirements

• Strong SQL skills and experience with data modeling approaches such as star schemas, snowflake schemas, or data vault.
• Practical experience with dbt or a comparable transformation framework.
• Hands-on Python experience and familiarity with orchestration tools such as Airflow, Dagster, or Prefect.
• Familiarity with cloud data warehouses and BI tools.
• Understanding of data quality, governance, and observability practices.
• Fluency in Spanish and English for collaboration with local and international teams.
• A degree in computer engineering, data engineering, data science, or a related field; strong communication and cross-functional collaboration skills.

Nice to have

• Experience working in a data mesh or federated data organization.
• Familiarity with data catalog platforms.
• Analytics experience in marketing, CRM, or B2B reporting.
• Experience or interest in using AI coding assistants for data development.

Benefits and work setup

• Home-office-friendly work setup, health insurance, stock options, and a compensation package that may include a performance bonus.
• Additional offerings include event discounts, English lessons, a gym membership, flexible remuneration, and the option to receive part of salary in advance.