Full job description
Mediavine is seeking a mid-level Data Engineer to build and maintain scalable data pipelines, manage transformation processes, and ensure data quality and security. The role involves coding in Python and SQL, developing on AWS, and using tools like Rundeck, Metabase, dbt, and Snowflake. Responsibilities include creating resilient data pipelines, leading technical projects, supporting data analysts and engineers, participating in code reviews, and implementing data quality and governance tooling. Requirements include 3+ years in data engineering, strong Python and SQL skills, cloud experience (AWS preferred), managing complex dbt environments, API data retrieval, DevOps collaboration, scheduler experience, and familiarity with multi-TB cloud data warehouses. The position is fully remote with comprehensive benefits, 401(k) matching, generous PTO, wellness initiatives, and professional development opportunities. Location is Atlanta, Georgia, United States with up to 15% travel.
What you'll do
- Create data pipelines that make data available for analytic and application use cases
- Develop self-healing, resilient processes that do not require constant care and feeding to run smoothly
- Create meaningful data quality notifications with clear actions for interested parties including other internal teams and other members of the data and analytics team
- Lead projects from a technical standpoint, creating project Technical Design Documents
- Support data analysts and analytics engineers ability to meet the needs of the organization
- Participate in code reviews, understanding coding standards, ensuring test coverage and being aware of best practices
- Build or implement tooling around data quality, governance and lineage, in the dbt framework and Snowflake but external to that as needed
- Provide next level support when data issues are discovered and communicated by the data analysts
- Work with data analysts and analytics engineers to standardize transformation logic in the dbt layer for consistency and ease of exploration by end users
- Enable analytics engineers and data analysts by providing data modeling guidance, query optimization and aggregation advice
Requirements
- 3+ years of experience in a data engineering role
- Strong Python skills (understands tradeoffs, optimization, etc.)
- Strong SQL skills (CTEs, window functions, optimization)
- Experience working in cloud environments (AWS preferred, GCS, Azure)
- Experience managing complex dbt environments with hundreds or more flows
- Understanding of how to best structure data to enable internal and external facing analytics
- Familiarity with calling APIs to retrieve data (authentication flows, filters, limits, pagination)
- Experience working with DevOps to deploy, scale and monitor data infrastructure
- Scheduler experience either traditional or DAG based
- Experience using LM-powered tools for code generation, documentation, and architectural diagramming
- Comfortable working with multi-TB cloud data warehouses (Snowflake preferred, Redshift, BigQuery)
- Experience with other DBMS systems (Postgres in particular)
- Ability to travel up to approx 15%
Tech stack
PythonSQLAWSGCSAzuredbtSnowflakeRedshiftBigQueryPostgresRundeckPrefectMetabaseSnowplowGoogle Ad ManagerOmniSigma
Benefits
100% remoteComprehensive benefits including Medical, Dental, Vision, Disability, and Life Insurance401(k) with company matchingGenerous PTOWellness initiatives and employer-sponsored mental health resourcesProfessional development opportunitiesInclusive, collaborative, and entrepreneurial company culture