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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer II - **Company:** Mediavine, Inc. - **Location:** Atlanta, GA, United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, User Authentication, Microsoft Azure, BigQuery, Cloud Database, Code Coverage, Code Generation, Code Review, Databases, Information Engineering, Data Infrastructure, Data Structures, Data Warehousing, Database Queries, DevOps, Python (Programming Language), PostgreSQL, Query Optimization, Simple Data Format, Snowplow, SQL Databases, Workflow Management Systems, Cloud Platform System, Snowflake, Maintaining Code, Rundeck, Software Coding, Pagination, Data Pipelines - **Published:** June 7, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=d9d0ea36b73e36a8 ## About the Role Do you have experience in Technical writing within technology?, * 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 * An 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, Big Query) * Experience with other DBMS systems (Postgres in particular) * Ability to travel up to approx 15% Nice to haves: * Experience with web analysis such as creating data structures that support product funnels, user behavior, and decision path analysis * Understanding of Snowflake external stages, file formats and snowpipe * Experience managing the semantic layer in either dbt or Snowflake * Experience with orchestration tools particularly across different technologies and stacks * Knowledge of Ad Tech, Google Ad Manager and all of its fun quirks (so fun) * The ability to make your teammates laugh (it wouldn't hurt if you were fun to work with is what I'm saying) * Familiarity with event tracking systems (Snowplow, etc) * Experience with one or more major BI tools (Omni, Sigma, Metabase, etc.) ## Description A Data Engineer at Mediavine will help build and maintain our data infrastructure. Building scalable data pipelines, managing transformation processes, and ensuring data quality and security at all steps along the way. This will include writing and maintaining code in Python and SQL, developing on AWS, and selecting and using third-party tools like Rundeck, Metabase, and others to round out the environment. You will be involved in decisions around tool selection and coding standards. Our current data engineering toolkit consists of custom Python data pipelines, AWS infrastructure including Kinesis pipelines, Rundeck scheduling converting to Prefect orchestration, dbt for transformation and Snowflake as our data warehouse platform. We are open to new tools and expect this position to be a part of deciding the direction we take. Essential Responsibilities * 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 * Leading 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 ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Making Data Warehouses fast. 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