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# Data Engineer

- **Company:** Aivra Health Llc
- **Location:** Seattle, WA, United States
- **Experience:** Starter
- **Salary:** $150,000.0 - $200,000.0
- **Contract:** Internship / Graduate position
- **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Amazon S3, Microsoft Azure, Big Data, BigQuery, Databases, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Python (Programming Language), MongoDB, NoSQL, Standard Sql, Data Processing, Google Cloud, Data Ingestion, Azure Data Factory, Snowflake, Apache Spark, Pyspark, Kubernetes, Information Technology, Apache Kafka, Restful APIs, Terraform, Data Pipelines, Docker, Databricks
- **Published:** September 25, 2026
- **Apply:** https://www.dice.com/job-detail/884ab7dd-2086-4897-94dc-2aa2d9538e10

## About the Role

* Python
 * SQL
 * ETL / ELT
 * Data Pipelines
 * Data Warehousing
 * Apache Spark / PySpark
 * AWS / Azure / Google Cloud Platform
 * Git / GitHub
 * Database fundamentals
 * Data Modeling
 * REST APIs, Master's degree in Computer Science, Data Engineering, Information Technology, Data Science, or a related technical field., * s and candidates with 1-3 years of experience.
 * Currently living in the USA.
 * Relevant data/technology experience through internships, projects, or professional work.
 * Valid US work authorization, where required(F1-OPT/STEM-OPT/H1-B).
 * Open to Work / actively seeking opportunities.

## Description

We are looking for a Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate should have strong SQL and Python skills and experience working with databases, cloud platforms, and data processing technologies., * Build and maintain scalable ETL/ELT pipelines.

 * Develop data ingestion and transformation workflows.
 * Design and optimize databases and data warehouses.
 * Process and analyze large datasets.
 * Ensure data quality, reliability, and security.
 * Integrate data from multiple sources and APIs.
 * Monitor and troubleshoot data pipelines.
 * Collaborate with Data Scientists, Software Engineers, and Business teams.
 * Implement automated data workflows and documentation., * Airflow
 * Databricks
 * Snowflake
 * Kafka
 * AWS S3 / Redshift / Glue
 * Azure Data Factory
 * BigQuery
 * Docker / Kubernetes
 * Terraform
 * CI/CD
 * dbt
 * NoSQL / MongoDB


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