> Markdown version of [/jobs/ext/2714300-data-engineer-master-data-dataops-edw](https://www.wearedevelopers.com/jobs/ext/2714300-data-engineer-master-data-dataops-edw). 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 - Master Data & DataOps (EDW)

- **Company:** Insight Global
- **Location:** Atlanta, GA, United States
- **Salary:** $104,000.0 - $124,800.0
- **Contract:** Permanent contract
- **Skills:** Airflow, BigQuery, Continuous Integration, Data Validation, Information Engineering, Extract Transform Load (ETL), Data Warehousing, DevOps, Data Flow Control, Github, Python (Programming Language), Online Analytical Processing, Open Data Protocol, DataOps, SQL*Plus, Google Cloud, Sql Optimization, Delivery Pipeline, Large Language Models, Data Layers, Containerization, Kubernetes, Data Management, Terraform, Data Pipelines, Jenkins
- **Published:** September 4, 2026
- **Apply:** https://www.atlantacareerpath.com/job.asp?id=3377270095&tx=JJ5145FFF&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

*Hands-on data engineering experience with a strong foundation in ETL/ELT, data modeling, orchestration, and cloud data ecosystems.

*Expert-level SQL plus solid Python in a data engineering context.

*Real GCP and BigQuery depth, including partitioning, clustering, and performance and cost optimization.

*Experience with Dataform or DBT for modeling and transformation.

*Exposure to CI/CD and infrastructure-as-code, ideally Jenkins, GitHub, and Terraform, for governed, repeatable deployments.

*A systemic thinker who can explain the trade-offs behind engineering decisions and improve on prior work.

Strong communication skills, since you will partner directly with product, engineering, and business stakeholders to gather requirements and validate outcomes. *Familiarity with master data management or metadata governance frameworks such as data contracts and open data standards.

*Experience with AtScale, semantic layers, or OLAP modeling.

*Exposure to Kubernetes, containerized workloads, or internal developer platforms.

*Comfort integrating LLM-based agents or modern AI tooling into data workflows to accelerate automation and improve data quality.

*Retail or e-commerce domain experience, or a background at high-velocity data companies such as Chewy, Amazon, Wayfair, or Netflix

## Description

*Build, maintain, and optimize scalable data pipelines on Google Cloud Platform using BigQuery, Dataform or DBT, Dataflow, GCS, Pub/Sub, and Cloud Composer (Airflow).

*Write advanced SQL for large-scale transformations, along with Python for automation, orchestration, and pipeline development.

*Support the master data layer that governs thousands of tables and their metadata, ensuring accuracy, lineage, and consistency at enterprise scale.

*Contribute to the DataOps and DevOps side of the platform through CI/CD pipelines (Jenkins, GitHub), infrastructure-as-code with Terraform, and GitOps-style deployment workflows.

*Implement change management, access controls, and self-service tooling that reduce friction for downstream data builders.

*Apply strong defensive engineering habits such as data validation, monitoring, schema checks, and alerting so pipelines run as reliably on day 100 as they do on day 1.


## 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)
- [The Road to MLOps: How Verivox Transitioned to AWS](https://www.wearedevelopers.com/videos/1050-the-road-to-mlops-how-verivox-transitioned-to-aws)
- [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)
- [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next)
- [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering)
- [Our GitOps approach for deploying an Identity Provider and an API Gateway in a SaaS company](https://www.wearedevelopers.com/videos/776-our-gitops-approach-for-deploying-an-identity-provider-and-an-api-gateway-in-a-saas-company)

## Related Articles

- [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)
- [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)
- [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)
- [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)
- [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud)
- [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)