> Markdown version of [/jobs/ext/226696-senior-data-engineer](https://www.wearedevelopers.com/jobs/ext/226696-senior-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).

---

# Senior Data Engineer

- **Company:** Benchmark
- **Location:** Chicago, IL, United States (Remote available)
- **Experience:** Expert
- **Salary:** $35,100.0 - $41,600.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Big Data, Cloud Engineering, Databases, Continuous Integration, Data Infrastructure, Extract Transform Load (ETL), Data Systems, DevOps, Django Web Framework, Amazon DynamoDB, Fault Tolerance, Python (Programming Language), PostgreSQL, NoSQL, Standard Sql, SQL Databases, Unstructured Data, Data Processing, Cloud Platform System, Large Language Models, Apache Spark, Electronic Medical Records, Git, Kubernetes, Functional Programming, Amazon Simple Queue Service (SQS), Data Pipelines, Docker, Legacy Systems
- **Published:** May 14, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f8cfebbb7e871628

## About the Role

Do you have experience in System design?, Do you have a Bachelor's degree?, * Bachelor's degree in STEM field or equivalent experience

 * 6+ years of experience building production-grade data systems, with demonstrated ownership of system design or major platform components
 * Strong experience building ETL/ELT pipelines across structured and unstructured data
 * Experience with cloud-based architectures (AWS preferred)
 * Strong SQL and data modeling skills
 * Strong Python engineering skills
 * Experience with Docker and orchestration frameworks (Airflow or equivalent)
 * Experience modernizing or migrating legacy systems
 * Proven ability to troubleshoot complex data issues
 * Sufficient understanding of DevOps practices (CI/CD, IaC)
 * Ability to manage multiple priorities in a fast-paced environment, * Experience designing scalable data solutions in production
 * Experience handling large data volumes and schema evolution
 * Proficiency in SQL and relational/analytical databases
 * Proficiency in Python (and/or Java, Shell)
 * Experience with AWS ecosystem (S3, Lambda, SQS/SNS)
 * Familiarity with Spark/EMR preferred
 * Experience with Docker and Kubernetes
 * Strong data modeling knowledge (relational and NoSQL)
 * Technologies: SQL, Python, AWS, Postgres, Spark/EMR, Git, Docker, Kubernetes, Django, DynamoDB

Preferred Qualifications

 * Experience building or contributing to a greenfield data platform
 * Experience migrating away from legacy ETL tools
 * Experience integrating LLM or agent-based systems into data workflows (e.g., tool-calling, retrieval, automation)
 * Experience working in regulated environments (e.g., GovCloud, HIPAA)

## Description

We are actively evolving our data platform from legacy ETL systems to a modern, cloud-native architecture built on Python, Kubernetes, and AI-assisted and agentic workflows. This role will play a critical part in that transformation., * Designing, developing, and maintaining scalable, fault-tolerant data pipelines and ETL/ELT processes across a modern stack

 * Contributing to the design and implementation of a greenfield data platform leveraging Python, Kubernetes, and AWS services
 * Operating in a hybrid greenfield and brownfield environment: building new capabilities while maintaining legacy systems
 * Leading development discussions and defining engineering patterns and standards
 * Assessing and analyzing legacy data processes and driving modernization efforts
 * Collaborating with cross-functional teams to ensure delivery of clean, reliable, and production-ready data
 * Improving data pipeline performance, observability, and reliability
 * Designing and integrating AI-assisted or agentic workflows to improve data processing and system interaction
 * Supporting documentation efforts for scalability and platform adoption
 * Providing technical mentorship and guidance to junior engineers
 * Acting as a technical SME in internal and client-facing discussions


## 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)
- [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)
- [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis)
- [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered)
- [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering)
- [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)
- [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)
- [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 Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk)
- [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)
- [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries)