> Markdown version of [/jobs/ext/654543-intl-india-etl-developer](https://www.wearedevelopers.com/jobs/ext/654543-intl-india-etl-developer). 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). --- # Intl - India - ETL Developer - **Company:** Insight Global - **Location:** Houston, TX, United States - **Experience:** Expert - **Salary:** $20,800.0 - $37,440.0 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Amazon S3, Continuous Integration, Data as a Services, Information Engineering, Data Governance, Extract Transform Load (ETL), Database Queries, Software Debugging, Python (Programming Language), NoSQL, Performance Tuning, DataOps, Unstructured Data, Workflow Management Systems, Apache Spark, Git, Data Lineage, AWS Data Analytics, Cloudwatch, Amazon Simple Queue Service (SQS), Data Pipelines, Databricks - **Published:** June 26, 2026 - **Apply:** https://www.juju.com/job/00000000gb3y6o ## About the Role 7-10 years of hands-on ETL/Data Engineering experience Strong expertise with Databricks and Apache Spark Solid experience across AWS data services (Glue, S3, Lambda, EMR, Athena, Secrets Manager) Strong SQL skills + experience with both relational and NoSQL stores Experience with CI/CD, Git, and modern data engineering best practices Strong debugging, performance tuning, and pipeline optimization skills Experience with Python/Scala for data workflows Familiarity with AWS orchestration tools (Kinesis, SNS/SQS, CloudWatch) Background in data quality frameworks and data lineage implementation Exposure to enterprise-scale analytics initiatives Knowledge of data modeling and job optimization techniques ## Description An Insight Global client has a role seeking a Senior ETL/Data Engineer to design, build, and optimize scalable data pipelines in an AWS-based ecosystem. This position focuses on high-performance ETL workflows leveraging Databricks, Spark, and AWS-native data services. The engineer will support ingestion, transformation, orchestration, data quality, and production reliability for enterprise analytics initiatives. Responsibilities include building and maintaining ETL pipelines, integrating structured/unstructured data, implementing monitoring frameworks, and collaborating with U.S.-based stakeholders to ensure robust, scalable solutions. ## Related Videos - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [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) - [NoSQL Data Modeling for Front-end Developers](https://www.wearedevelopers.com/videos/297-nosql-data-modeling-for-front-end-developers) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [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)