> Markdown version of [/jobs/ext/509637-data-engineer](https://www.wearedevelopers.com/jobs/ext/509637-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Edi Architecture Inc - **Location:** Texas City, TX, United States - **Salary:** $111,737.0 - $134,565.0 - **Contract:** Permanent contract - **Skills:** Agile Methodology, Amazon Web Services, Microsoft Azure, BigQuery, Cloud Computing, Databases, Continuous Integration, Data Infrastructure, Extract Transform Load (ETL), Data Warehousing, DevOps, Apache Hadoop, Python (Programming Language), Machine Learning, SQL Databases, Snowflake, Apache Spark, Data Lakes, Stream Processing, Data Pipelines, Amazon Redshift, Databricks - **Published:** June 7, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=82f7476cf0abb572 ## About the Role Do you have experience in Schema design?, Python, SQL, and Data Modeling Apache Spark, Hadoop, or Databricks Cloud Platforms (AWS, Azure, or GCP) Data Warehousing (Snowflake, Redshift, BigQuery) ETL Tools and Workflow OrchestrationStrong understanding of database architecture Preferred Qualifications: * Experience with real-time data processing * Knowledge of CI/CD and DevOps practices * Experience working in Agile environments * Exposure to Machine Learning data pipelines is a plus ## Description * Design, develop, and maintain scalable ETL/ELT pipelines * Build and optimize data warehouses and data lakes * Work with large-scale structured and unstructured datasets * Collaborate with Data Scientists, Analysts, and Business Teams * Ensure data quality, reliability, security, and governance * Monitor and improve data platform performance ## 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) - [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) - [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) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Making Data Warehouses fast. A developer's story.](https://www.wearedevelopers.com/videos/302-making-data-warehouses-fast-a-developer-s-story) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)