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# Data Engineer

- **Company:** Pyramid Consulting Inc.
- **Location:** Rutherford, NJ, United States
- **Experience:** Expert
- **Salary:** $135,200.0 - $141,440.0
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Cloud Computing, Computer Programming, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Distributed Computing Environment, Python (Programming Language), Machine Learning, Query Optimization, SQL Databases, Data Processing, Apache Spark, Generative AI, Data Lakes, Data Management, Data Pipelines
- **Published:** October 7, 2026
- **Apply:** https://www.dice.com/job-detail/f8838281-755c-4ed9-8af9-249b07546d51

## About the Role

* Skills - Data Modeling, SQL, Python, Apache Spark, Data Warehouses and/or Data Lakes, Generative AI (GenAI), Google ADK, ETL/ELT
 * Strong hands-on experience with Data Modeling.
 * Advanced proficiency in SQL and query optimization.
 * Strong programming skills in Python.
 * Practical experience with Apache Spark and distributed data processing.
 * Experience working with Data Warehouses and/or Data Lakes.
 * Strong understanding of data engineering concepts, pipeline architecture, and data management practices.
 * Exposure to Generative AI (GenAI) technologies and use cases.
 * Understanding of Machine Learning concepts and workflows.
 * Experience with Google ADK.
 * Hands-on experience with major Cloud Platforms.
 * Familiarity with ETL/ELT frameworks and tools.

## Description

* Architect, develop, and maintain robust and scalable data pipelines and data engineering solutions.
 * Design and implement logical and physical data models to support business and analytical requirements.
 * Build efficient data processing solutions using Python and Apache Spark.
 * Improve data pipeline performance, reliability, data quality, and governance.
 * Work closely with application, analytics, and business stakeholders to understand and translate data requirements into technical solutions.
 * Contribute to data initiatives supporting AI/ML use cases, advanced analytics, and reporting.
 * Identify opportunities to improve existing data architecture, processes, and engineering practices.