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# Data Engineer

- **Company:** Robert Half
- **Location:** Memphis, TN, United States
- **Experience:** Experienced
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Computing, Cloud Engineering, Continuous Integration, Data Validation, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Warehousing, Relational Databases, Database Development, DevOps, Dimensional Modeling, JSON, Python (Programming Language), PostgreSQL, Machine Learning, Microsoft SQL Server, MySQL, Oracle (Applications), Power BI, Cloud Services, SQL Databases, Tableau (Software), Workflow Management Systems, Software Organization, Data Processing, Google Cloud, Enterprise Software Applications, Azure Data Factory, Database Optimization, Database Performance, Indexer, Git, Data Lakes, Semi-structured Data, Information Technology, Restful APIs, Stream Processing, Data Inconsistencies, Data Pipelines
- **Published:** November 5, 2026
- **Apply:** https://www.memphisjobforce.com/job.asp?id=3496680979&tx=JK8579FFQ&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

* Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field, or equivalent practical experience.
 * 3-5+ years of professional experience in data engineering, database development, or related roles.
 * Strong proficiency in SQL and Python.
 * Hands-on experience developing ETL/ELT pipelines and data integration solutions.
 * Experience working with relational databases such as SQL Server, PostgreSQL, Oracle, or MySQL.
 * Experience with cloud platforms such as AWS, Azure, or Google Cloud.
 * Knowledge of data warehousing concepts, dimensional modeling, and database optimization.
 * Experience with data orchestration and scheduling tools.
 * Familiarity with REST APIs, JSON, and other data integration methods.
 * Experience with Git, CI/CD, and software development best practices.
 * Strong analytical, troubleshooting, and communication skills.

## Description

Data Pipeline Development & Integration

 * Design, build, and maintain scalable ETL/ELT pipelines to extract, transform, and load data from multiple sources.
 * Develop automated data integration solutions supporting enterprise applications, analytics, and reporting.
 * Integrate structured and semi-structured data from APIs, relational databases, cloud platforms, and third-party systems.
 * Develop batch and real-time data processing solutions.
 * Troubleshoot pipeline failures, data inconsistencies, and performance bottlenecks.

Data Warehousing & Architecture

 * Design and optimize enterprise data warehouses, data lakes, and lakehouse architectures.
 * Develop efficient data models, schemas, and transformations to support business intelligence and analytics.
 * Build and maintain cloud-based data solutions using AWS, Microsoft Azure, or Google Cloud.
 * Optimize SQL queries, database performance, and data processing workloads.
 * Implement data partitioning, indexing, and storage optimization strategies.

Data Quality & Governance

 * Develop automated data validation, monitoring, and quality assurance processes.
 * Ensure data accuracy, consistency, reliability, and availability across enterprise systems.
 * Implement data governance standards, access controls, and security best practices.
 * Maintain documentation for data pipelines, architecture, and transformation logic.
 * Support compliance with organizational data privacy and security requirements.

Cloud Engineering & Automation

 * Develop and maintain cloud-native data pipelines and processing workflows.
 * Utilize orchestration tools such as Apache Airflow, Azure Data Factory, or similar technologies.
 * Implement CI/CD practices for data engineering workflows.
 * Automate data processing, monitoring, and infrastructure deployment.
 * Collaborate with DevOps and infrastructure teams to improve scalability and reliability.

Analytics & AI Support

 * Partner with business intelligence and analytics teams to deliver reliable datasets for reporting and dashboards.
 * Develop curated data models supporting Power BI, Tableau, and other visualization platforms.
 * Build data pipelines supporting machine learning, predictive analytics, and AI applications.
 * Collaborate with AI engineers and data scientists to prepare, transform, and deliver data for model development and production applications.
 * Identify opportunities to improve business processes through better data integration and automation.