> Markdown version of [/jobs/ext/4013086-data-management-and-analytics-engineer](https://www.wearedevelopers.com/jobs/ext/4013086-data-management-and-analytics-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 Management and Analytics Engineer

- **Company:** Indotronix Avani Group
- **Location:** Remote, OR, United States (Remote available)
- **Experience:** Expert
- **Contract:** Temporary to permanent
- **Skills:** Microsoft Word, Artificial Intelligence, Information Engineering, Power BI, Collibra, Data Management
- **Published:** October 29, 2026
- **Apply:** https://candidateportal.ceipal.com/job-details/at5C2RBaNHHyjf1Cuxm8yQbnFyw8E4TJpz8MhwP5mNM

## About the Role

5-8+ years in data engineering, cloud data platforms, and enterprise data integration.

 - Advanced proficiency in SQL, Python, ETL/ELT, and data modeling.
 - Hands-on experience with Snowflake or similar cloud data platforms.
 - Strong focus on data quality, metadata management, and data lineage.
 - Practical knowledge of Git, CI/CD, and REST APIs.

Preferred Skills

 - Familiarity with Kafka, Change Data Capture (CDC), dbt, Collibra, Ataccama, Power BI, AWS, OpenShift, and Kubernetes.
 - Exposure to GenAI, Agentic AI, Retrieval-Augmented Generation (RAG), knowledge graphs, ontologies, and semantic models., Word

## Description

Join our dynamic team as a Data Management and Analytics Engineer and drive the future of data-driven solutions. You'll work with modern cloud data platforms, engineer robust data pipelines, and collaborate with analytics and AI teams to shape innovative business outcomes. This is a remote, contract-to-hire opportunity designed for experienced professionals seeking impactful projects and growth in a collaborative environment., Architect, build, and optimize scalable data pipelines using SQL, Python, ETL/ELT frameworks.

 - Develop and maintain data solutions on Snowflake and leading cloud platforms.
 - Implement data modeling, ensure high data quality, and manage metadata and data lineage.
 - Integrate data sources via APIs and support both batch and real-time data processing.
 - Utilize Git, CI/CD pipelines, and automated testing for seamless deployment.
 - Collaborate with analytics, data governance, and AI teams to deliver trusted and actionable data solutions.