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# Senior Data Engineer

- **Company:** Insight Global
- **Location:** Nashville, TN, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Sql Data Warehouse, Airflow, Amazon Web Services, Microsoft Azure, Continuous Integration, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Warehousing, Python (Programming Language), Performance Tuning, Standard Sql, DataOps, Workflow Management Systems, Snowflake, Apache Spark, Data Management, Data Pipelines
- **Published:** October 2, 2026
- **Apply:** https://dejobs.org/x/x/1511BF8B11BC42498582F56329E299DF/job/

## About the Role

* 4+ years of experience in data engineering or data warehousing * Strong experience with Snowflake, dbt, Fivetran, Python, and SQL * Experience building and maintaining data pipelines and ETL/ELT processes * Solid understanding of data modeling best practices in cloud data warehouse environments * Ability to troubleshoot performance issues and optimize queries * AWS or Azure Strong communication skills and ability to work cross-functionally * Experience with orchestration tools (e.g., Airflow) * Exposure to CI/CD practices and infrastructure-as-code * Familiarity with data governance frameworks Experience with big data tools like Spark

## Description

Insight Global is looking for a Senior Data Engineer to support one of our financial services clients in Nashville, TN. This individual will join a growing data team focused on building and optimizing data pipelines, transforming data for analytics, and ensuring high-quality, reliable data is available for business intelligence initiatives. This is a hands-on role ideal for someone who enjoys working with modern data tools and collaborating across technical and business teams. Responsibilities: * Design, build, and maintain scalable data pipelines to ingest data from multiple sources * Develop and optimize data transformation models using dbt * Ensure data quality, accuracy, and reliability through testing and monitoring * Implement best practices for data modeling and warehouse performance * Partner with analysts, engineers, and business stakeholders to understand data needs Contribute to internal processes, documentation, and overall data engineering best practices


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