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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Cross Screen Media, LLC - **Location:** Alexandria, VA, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Unit Testing, Cloud Database, Static Program Analysis, Data Architecture, Information Engineering, Extract Transform Load (ETL), Database Queries, Python (Programming Language), Snowflake, Data Layers, Information Technology, Data Pipelines - **Published:** August 9, 2026 - **Apply:** https://www.wayup.com/i-j-Data-Engineer-Cross-Screen-Media-917217919109090/ ## About the Role + BS in Computer Science or equivalent + 5+ years experience in software/data engineering + Strong SQL skills + Experience with ETL/ELT techniques + Strong sense for data architecture - you can look at a set of requirements and reason about how data should be modeled, where it should live, and how schemas should be designed for clarity and reuse + Experience with dbt + Experience with Airflow or similar orchestration tools + Experience with Snowflake or similar cloud data warehouses + Experience working with AWS + Unix/Linux fundamentals + Nice to have: Experience with AI coding tools + Nice to have: Exposure to ad tech concepts & terminology ## Description Cross Screen Media is founded by industry veterans and gives customers a new way to plan and execute video advertising campaigns. To achieve this, we need an amazing team. Here's where you come in… We are looking to hire a Data Engineer with a strong work ethic and a passion for the fast-paced startup life. The ideal candidate doesn't just build pipelines - they think critically about how data should be modeled, how systems connect, and how to design for scale. You'll work alongside a senior data engineer and collaborate across a small, high-output team to shape the data layer behind our product, ScreenSolve. We're currently using tools and platforms like Python, Airflow, dbt, AWS and Snowflake. This is a fully remote position. Face to face communication is important to us, so we have quarterly in-person team meetings at our office in Alexandria, VA. Additionally, we have biannual company offsites to give all of our employees time together in person., + Design and develop data pipelines, with an eye toward how they fit into the broader data architecture + Make data modeling and schema design decisions - choosing the right structure for how data is stored, accessed, and extended + Think beyond the immediate task: consider how today's integration point becomes tomorrow's platform surface area + Deliver features rapidly using AI-assisted development tools (Claude Code, etc.) + Contribute to definition of user stories + Collaborate with other members of the team on development & integration + Write unit tests and maintain high code quality, per both static code analysis & team standards + Be available on a rotating schedule for production issues ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Why Your AI Agent Keeps Hallucinating Your Data: Building Deterministic Context Layers](https://www.wearedevelopers.com/videos/2055-why-your-ai-agent-keeps-hallucinating-your-data-building-deterministic-context-layers) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 139 - Soft and hard queries](https://www.wearedevelopers.com/magazine/487-dev-digest-139-soft-and-hard-queries) - [Dev Digest 162: AI careers, MCP, AWS best practices & floppy sweaters](https://www.wearedevelopers.com/magazine/571-dev-digest-162-ai-careers-mcp-aws-best-practices-floppy-sweaters)