> Markdown version of [/jobs/ext/4203502-data-engineer](https://www.wearedevelopers.com/jobs/ext/4203502-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:** Insight Global - **Location:** Irving, TX, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Asana, JIRA, Microsoft Azure, Big Data, Information Engineering, Data Governance, Data Integration, Data Systems, Data Warehousing, Dimensional Modeling, Python (Programming Language), Power BI, SQL Databases, Tableau (Software), Snowflake, Technical Debt, Data Analytics, Looker Analytics, Data Pipelines, Databricks - **Published:** October 26, 2026 - **Apply:** https://dejobs.org/x/x/D27877C5A27147398B028DDB773B0385/job/ ## About the Role 2+ years of experience in data engineering, analytics engineering, or a related field 2+ years of hands-on experience with Databricks or Snowflake, with Databricks preferred Strong Python and SQL experience Experience building and maintaining data pipelines Experience with data quality, validation, and large/complex datasets Understanding of dimensional modeling, star schemas, and data warehousing Familiarity with data governance, lineage, and production support Azure APIs/data integrations Dimensional modeling/star schemas Power BI, Tableau, or Looker Jira or Asana ## Description The Data Analytics Engineer will build, maintain, and improve scalable data solutions supporting US Oncology analytics and operational reporting. This role will work hands-on with Databricks, Python, and SQL to develop data pipelines, strengthen data quality, reduce technical debt, and build consolidated datasets. The engineer will also support dimensional modeling, data integrations, lifecycle management, documentation, troubleshooting, and production support while partnering with technical and business stakeholders to deliver reliable and reusable data solutions.