Senior Data Engineer — Cloud-Native Data Platform Leader

evolvevacationrental; EE. UU.; A distancia; USD 155.000 - 165.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

401(k) match

Equity

Parental leave

Health care coverage

PTO & holidays

Travel discounts

Growth opportunities

Descripción de la vacante

Evolve is seeking a Senior Data Engineer to lead the design and evolution of our data platform. You’ll shape scalable data pipelines and architectures supporting analytics, reporting, and ML workloads, while driving cost efficiency and performance improvements.

You will mentor others, collaborate with DevOps and Cloud teams on AWS infrastructure, and advocate best practices in CI/CD, testing, and data quality. A strong data mindset and modern stack fluency are essential.

Formación

• 8+ years in data engineering, architecture, or related technical roles.
• Deep experience with SQL and Python for data transformation and automation.
• Hands-on experience with modern data stack tools such as dbt, Airbyte, Fivetran, and Snowflake.

Responsabilidades

• Serve as a senior technical contributor shaping scalable, modular data systems.
• Partner with cross-functional teams to design reliable data pipelines for analytics and data science.
• Develop and optimize ELT workflows using Airbyte, Fivetran, dbt, and Python.
• Design and maintain data models in Snowflake to support clean datasets.
• Lead data observability efforts with proactive alerting and incident response.

Conocimientos

SQL

Python

Data modeling

Data pipelines

Snowflake

dbt

Airbyte

Fivetran

Airflow

AWS

Observability

Herramientas

dbt

Airbyte

Fivetran

Snowflake

Descripción del empleo

Evolve is seeking a Senior Data Engineer to lead the design and evolution of our data platform. You’ll shape scalable data pipelines and architectures supporting analytics, reporting, and ML workloads, while driving cost efficiency and performance improvements.

You will mentor others, collaborate with DevOps and Cloud teams on AWS infrastructure, and advocate best practices in CI/CD, testing, and data quality. A strong data mindset and modern stack fluency are essential.