Senior Data Engineer: Cloud Data Pipelines & Analytics Lead

Evolve; United States; On-site; USD 155,000 - 165,000; Full time

Benefits offered by this job

401(k) with 4% match

Parental leave (16-18 weeks)

Health, dental, vision plans

Generous PTO & holidays

Travel perks & stay discounts

Learning & development programs

Employee Resource Groups

Job summary

Evolve seeks a Senior Data Engineer in the United States to design and evolve our data ecosystem, enabling analytics, reporting, and ML workloads. You’ll lead architectural decisions, build scalable pipelines, and mentor others while driving cost efficiency and performance.

You’ll work with a modern stack (Snowflake, dbt, Airflow, Airbyte, Fivetran) within an AWS-based environment, shaping data models and observability across the platform.

Qualifications

• 6+ years in data engineering, architecture, or related roles with large-scale data systems.
• Deep experience with SQL and Python for data transformation and automation.
• Hands-on with modern data stack tools such as dbt, Airbyte, Fivetran, and Snowflake.
• Strong understanding of cloud technologies, especially AWS services.

Responsibilities

• Serve as a senior technical contributor shaping scalable data systems.
• Partner with cross-functional teams to design 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 (star schemas, dimensional modeling).
• Lead efforts to improve data observability with monitoring and incident response.

Skills

SQL

Python

Snowflake

dbt

Airbyte

Fivetran

Airflow

Git CI/CD

Communication

Tools

dbt

Airbyte

Fivetran

Snowflake

Airflow

Iceberg

AWS

Job description

Evolve seeks a Senior Data Engineer in the United States to design and evolve our data ecosystem, enabling analytics, reporting, and ML workloads. You’ll lead architectural decisions, build scalable pipelines, and mentor others while driving cost efficiency and performance.

You’ll work with a modern stack (Snowflake, dbt, Airflow, Airbyte, Fivetran) within an AWS-based environment, shaping data models and observability across the platform.