Senior Data Engineer at Evolve

Job description

At Evolve , we’re on a mission to make vacation rental easy for everyone. Our high-performing, customer-obsessed team runs on curiosity, communication, and accountability—working together to create exceptional experiences for our owners and guests. Whether solving big challenges, delivering outstanding results, or celebrating wins, we approach every day with purpose and passion. If you’re ready to join a mission-driven company where every teammate has the opportunity to thrive, Evolve might just be the place for you. Why This Role 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. What You'll Do 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. What Makes You a Great Fit 6+ 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. Compensation Annual base salary range: $155,000-$165,000, depending on experience and qualifications. This role is also eligible for a variable annual bonus based on both company and individual performance. Location All Evolve team members must live in one of our approved locations by their first day. We can hire from anywhere in the U.S. except D.C. and Hawaii. Some positions may also have restrictions based on compensation in the following states: California, Maryland, New York, Pennsylvania, Rhode Island, and Washington. If you live in Colorado, you can work remotely anywhere in the state, at our downtown Denver office, or a hybrid of both! If you're planning to move soon, please let us know, and we'll be happy to review your application again. California Applicant Privacy Policy | Evolve How we reward Evolvers We’re intentional about offering benefits that empower every Evolver to thrive both professionally and personally because they’re more than perks—they’re investments in our customer-obsessed, high-performing team. We believe in treating others as they want to be treated, providing benefits that deliver real value, and challenging the status quo to meet the diverse needs of our team. Whether it’s helping you take care of your health, plan for the future, or celebrate life’s milestones, our offerings are designed to support you every step of the way. Financial Wellness: Industry-competitive pay, equity in the company, and a 401(k) with a 4% immediate vesting match. Family Support: 16-18 weeks of paid parental leave for birthing parents and 10 weeks for non-birthing parents, plus infertility coverage. Health & Wellness: Comprehensive medical, dental, and vision plans, with 100% employer-paid dental and vision for individual coverage, a low-cost medical option, 10 free mental health visits, and pet insurance. Time to Recharge: Generous PTO, RTO (for full-time exempt employees), sick leave, holidays, and a personal holiday to celebrate what matters most to you. Travel Perks: Annual Evolve travel credit after one year and discounts on stays at all Evolve properties. Growth Opportunities: World-class onboarding programs, learning, and development resources to help you grow your impact. Connection: Employee Resource Groups celebrating our diverse communities at Evolve. How we work together With our core values as our guide, every Evolver helps shape the company we want to work for and the people we want to be. We’ve cultivated a culture of collaboration, care, and responsibility that we can all be proud of, and we’re excited to see what you’ll bring as your authentic self. Still curious about who we are and what we do? Read more about our business and our culture at evolve.com . EEO At Evolve, we are committed to diversity and inclusion. As an equal opportunity employer, all qualified candidates will be considered for employment without regard to race, color, creed, religion, age, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression, sexual orientation, marital status, national origin, ancestry, citizenship status, military service or veteran status, physical or mental disability, or any other legally protected characteristic. Evolve participates in e-Verify for all positions. If you have a disability or special need that requires accommodation at any point in the hiring process, please let your recruiter know.

Requirements

Must-haves

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.
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.
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.
What Makes You a Great Fit
6+ 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.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaccessibilitypythonaisqlawsci/cd

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Parental Leave

Wellness