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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Platform Engineer - **Company:** Craft - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $170,000.0 - **Contract:** Permanent contract - **Skills:** Computer-Aided Design, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Code Generation, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Cursor (Graphical User Interface Elements), Programming Tools, Distributed Computing Environment, Amazon DynamoDB, Elasticsearch, Fault Tolerance, Github, Python (Programming Language), PostgreSQL, Machine Learning, Systems Development Life Cycle, Software Engineering, SQL Databases, Data Streaming, Unstructured Data, Circleci, Data Processing, Data Strategy, Pandas, Data Lakes, Pyspark, Terraform, Code Restructuring, Data Pipelines, Docker, Databricks - **Published:** August 20, 2026 - **Apply:** https://jobs.ashbyhq.com/craft.co/005e2bfe-2bcb-4009-b1e7-62d90ef18c7c?utm_source=NKjPjRxbrj ## About the Role * 4+ years of experience in Data Engineering. * 4+ years of experience with Python. * Experience in developing, maintaining, and ensuring the reliability, scalability, fault tolerance, and observability of data pipelines in a production environment. * Have fundamental knowledge of data engineering techniques: ETL/ELT, batch and streaming, DWH, Data Lakes, distributed processing. * Strong knowledge of SDLC and solid software engineering practices. * Familiar with infrastructure-as-code approach. * Demonstrated curiosity through asking questions, digging into new technologies, and always trying to grow. * Strong problem solving and the ability to communicate ideas effectively. * Self-starter, independent, likes to take initiative. * Familiarity with at least some of the technologies in our current tech stack: + Python, PySpark, Pandas, SQL (PostgreSQL), ElasticSearch, Airflow, Docker + Databricks, AWS (S3, Batch, Athena, RDS, DynamoDB, Glue, ECS, Amazon Neptune) + CircleCI, GitHub, Terraform * Knowledge surrounding AI-assisted coding and experience with Cursor, Co-Pilot, or Codex * A strong track record of leveraging AI IDEs like Cursor to: + Rapidly scaffold components and APIs + Refactor legacy codebases efficiently + Reduce context-switching and accelerate documentation + Experiment and prototype with near-instant feedback ## Description We're growing quickly and looking to hire several senior-level data engineers for multiple teams. Each team is responsible for a key product within the organization. As a core member of the team, you will have great say in how solutions are engineered and delivered. Craft gives engineers a lot of responsibility and authority, which is matched by our investment in their growth and development. Our data engineers carry a lot of software engineering responsibilities, so we're looking for engineers who have strong Python coding experience, Pandas expertise, and solid software engineering practices. What You'll Do: * Build and optimize data pipelines (batch and streaming). * Extracting, analyzing and modeling rich and diverse datasets of structured and unstructured data. * Design software that is easily testable and maintainable. * Support in setting data strategies and our vision. * Keep track of emerging technologies and trends in the Data Engineering world, incorporating modern tooling and best practices at Craft. * Work on extendable data processing systems that allows to add and scale pipelines. * Apply machine learning techniques such as anomaly detection, clustering, regression classification, and summarization to extract value from our data sets. * Leverage AI-powered development tools (e.g. Cursor) to accelerate development, refactoring, and code generation. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [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) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [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) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [The Best X (Twitter) Accounts for Developers](https://www.wearedevelopers.com/magazine/294-the-best-x-twitter-accounts-for-developers)