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# Data Engineer II

- **Company:** Sirian Group Inc
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Amazon S3, Microsoft Azure, Code Review, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Warehousing, Python (Programming Language), Machine Learning, Performance Tuning, SQL Databases, Talend, Workflow Management Systems, Google Cloud, Feature Engineering, Data Lakes, AWS Glue, AWS Data Analytics, Data Management, Data Pipelines, Amazon Redshift, Databricks
- **Published:** June 23, 2026
- **Apply:** https://www.dice.com/job-detail/5a9368ee-e02d-4d74-bf22-a7bee21fa032

## About the Role

9+ years of experience in Data Engineering, data platform development, or related roles, with strong proficiency in SQL and Python for data processing and pipeline development.

## Description

We are seeking a Data Engineer II to design, build, and maintain scalable data pipelines and data infrastructure that support analytics, reporting, and machine learning initiatives. The ideal candidate has strong experience in SQL, AWS data analytics services, and Python, with hands-on experience building ETL/ELT pipelines using modern cloud-based tools., * Design, develop, and maintain scalable ETL/ELT data pipelines using Python, SQL, and Apache Airflow.

 * Build and optimize data warehouses and data lakes using AWS Redshift, S3, and related AWS services.
 * Develop and manage data integration workflows using tools such as Airflow, Python, AWS Glue or Talend (optional).
 * Ensure data quality, reliability, and performance across pipelines and data platforms.
 * Optimize SQL queries, Redshift schemas, and data models for performance and scalability.
 * Prepare and deliver datasets for machine learning models for Forecasting usecases.
 * Implement CI/CD pipelines for data workflows and infrastructure deployments.
 * Monitor pipeline performance and troubleshoot production issues.
 * Maintain proper documentation and adhere to data governance and security best practices.
 * Participate in code reviews and contribute to improving engineering standards.
 * Experience with one or more cloud providers: AWS (Glue, S3, Redshift), Azure (Data Lake, Databricks), or Google Cloud Platform.
 * Experience with workflow orchestration tools such as Apache Airflow.
 * Familiarity with machine learning data pipelines or feature engineering workflows.
 * Understanding of data modeling, data warehousing concepts, and performance optimization.


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