Senior Data Engineer

Evolve

14d•$155,000 - $165,000•Remote

About The Position

At Evolve, data powers every aspect of how we transform the vacation rental industry. From optimizing guest experiences to enabling smarter homeowner engagement, our data platform supports scalable decision-making, operational excellence, and future-forward innovation. As a Senior Data Engineer, you'll be a key technical leader responsible for building and evolving our data ecosystem. You'll help design and optimize pipelines and architecture that support core reporting, analytics, and machine learning workloads, while also leading initiatives focused on cost efficiency, performance, and data accessibility. This role is ideal for an engineer who is passionate about modern data architecture, cloud-native infrastructure, and mentoring others while delivering high-impact systems that make data a true asset.

Requirements

8+ years in data engineering, architecture, or related technical roles working with large-scale data systems.
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.
Strong understanding of cloud technologies, particularly AWS (e.g., S3, Lambda, EC2, IAM).
Familiarity with open data formats and scalable data lakehouse principles (e.g., Iceberg or similar).
Experience building and operating workflow orchestration tools such as Airflow.
Knowledge of observability and monitoring frameworks to support data platform health and alerting.
Comfortable working in Git-based environments with strong CI/CD practices.
Ability to communicate technical concepts effectively to both technical and non-technical audiences.
Demonstrated ability to mentor, coach, and collaborate across a multidisciplinary data team.

Responsibilities

Serve as a senior technical contributor helping shape the design of scalable, modular, and performant data systems.
Partner with cross-functional teams to design and deliver reliable data pipelines for analytics, reporting, and data science use cases.
Develop and optimize ELT workflows using modern tools such as Airbyte, Fivetran, dbt, and Python.
Design and maintain performant data models in Snowflake, including star schemas and other dimensional modeling techniques that support clean, well-structured, and easily consumable datasets - including those optimized for AI tools and text-to-SQL interfaces.
Lead efforts to improve data observability, including proactive alerting, monitoring, and incident response capabilities.
Explore and implement open table formats (e.g., Apache Iceberg) to enable flexibility, scalability, and interoperability across data systems.
Collaborate with DevOps and Cloud teams to ensure our AWS-based infrastructure is optimized for performance, cost, and reliability.
Establish and maintain engineering best practices, including version control, code reviews, CI/CD pipelines, and automated testing.
Act as a mentor to other engineers and analytics professionals, fostering knowledge sharing and high standards for quality and consistency.
Stay current on emerging technologies and bring forward recommendations for improving platform capabilities, performance, or efficiency.