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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** THE MARKETING PRACTICE INC. - **Location:** United States (Remote available) - **Experience:** Experienced - **Salary:** $130,000.0 - $180,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Automation of Tests, Cloud Database, Data Validation, Extract Transform Load (ETL), Data Visualization, Software Debugging, Python (Programming Language), Operational Databases, Query Optimization, Software Engineering, SQL Databases, Production Code, Tools for Reporting, Software Version Control - **Published:** September 23, 2026 - **Apply:** https://www.builtincolorado.com/job/data-engineer/11322217?handler=ApplyRedirect ## About the Role * 3+ years of experience building and maintaining production data pipelines in high-growth, fast-paced environments. * Fluent in Python and SQL, with the ability to write, test, and debug production code and complex queries. * Proficient in cloud data warehousing, including schema design, incremental data loading, query optimization, and cost management. * Experience with extraction, transformation, loading, scheduling, and monitoring. * Knowledge of established data-quality practices, including input validation, automated testing, monitoring, documentation, version control, and reproducible outputs. * Skilled at translating business or research needs into clearly scoped technical requirements, deliverables, and implementation plans. * Demonstrated ability to communicate technical tradeoffs, project status, data limitations, and delivery risks to technical and nontechnical stakeholders. * Hands-on experience with AI-enabled tools supporting software development, data analysis, testing, documentation, or workflow automation. * Sound technical judgment when evaluating datasets and engineering approaches against downstream reporting, research, or product requirements. Bonus * Experience working with energy, finance, transaction, or market intelligence data. * Exposure to research, forecasting, survey analysis, or data-intensive publications. * Hands-on involvement in developing or supporting analytical or statistical models. * Knowledge of model testing and data-validation practices, including documenting assumptions and handling missing values and outliers. * Familiarity with data visualization, business intelligence, or reporting tools. ## Description * Own the Market Intelligence data foundation. Build and maintain the pipelines our market intelligence work runs on: survey responses, pricing series, volume and capacity forecasts, buyer participation. Extraction, transformation, scheduling, monitoring, the whole path. * Automate our survey processes end to end. Ingesting, cleaning, joining - a lot of this is ad hoc today. You will make it a system, so that scaling our survey program does not mean scaling hours of manual cleanup. * Get data where it needs to be. Supporting the reporting layer so that findings are visible and plugged into the tools, dashboards, and publications that depend on them, without an analyst stitching it together each time. * Turn recurring questions into repeatable queries. As bespoke research scales, you will be the person who will help productize. * Firm up Crux's data practices. With the data foundation in place, you'll help move it onto firmer ground: validating inputs, documenting assumptions, version control, reproducible outputs, finding and driving additional use cases across other teams. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Tomorrow's cloud data platforms - fully managed database-as-a-service (DBaaS)](https://www.wearedevelopers.com/videos/254-tomorrow-s-cloud-data-platforms-fully-managed-database-as-a-service-dbaas) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) - [TiDB, One Layer at a Time: How Distributed SQL Became an Agentic AI Backbone](https://www.wearedevelopers.com/videos/100117-tidb-one-layer-at-a-time-how-distributed-sql-became-an-agentic-ai-backbone) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1520-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)