Senior Data Engineer
New
E
EvolveVacation Rental
We can hire from anywhere in the U.S. except D.C. and Hawaii.Full-TimeSenior
SalaryAnnual 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.
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Job Details
- Experience
- 8+ years
- Required Skills
- AWSPythonSQLGitSnowflakeAirflowCI/CDdbt
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.
- 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.
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