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# Data Engineer III or IV (Databricks, Snowflake)

- **Company:** ConsultNet
- **Location:** Dallas, TX, United States
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Microsoft Azure, Cloud Computing, Cloud Database, Continuous Integration, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Systems, Data Warehousing, DevOps, Apache Hive, Python (Programming Language), Machine Learning, Performance Tuning, Systems Development Life Cycle, Scala (Programming Language), Software Engineering, SQL Databases, Transact-SQL, Scripting, Cloud Platform System, Feature Engineering, Azure Data Factory, Spring Cloud, Snowflake, Generative AI, Git, Pyspark, Star Schema, Data Management, Data Lakehouse, Azure Synapse Analytics, Data Pipelines, Databricks, Programming Languages
- **Published:** October 22, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-engineer-iii-or-iv-databricks-snowflake-dallas-tx--68ac67e2-c549-46fd-b738-00c3697d15e6

## About the Role

Snowflake Schema, Business Intelligence, Automation, Scalable System Development, DevOps, Software Engineering, Microsoft Windows Azure, Scala Programming Language, Best Practices, Python Programming/Scripting Language, Our client is seeking a highly motivated and accomplished Cloud Data Engineer with expertise in Azure Databricks, Azure Synapse Analytics, SQL, and cloud-based data platforms. The ideal candidate will have experience designing, developing, and optimizing scalable data lakehouse and data warehousing solutions that support enterprise reporting, analytics, and business intelligence. Strong technical skills in Python, PySpark, SQL, T-SQL, and Scala are required, along with experience building high-volume ETL/ELT pipelines, developing highly scalable and reusable Databricks notebooks, and leveraging Azure DevOps, Git, CI/CD, and cloud automation best practices to deliver secure and efficient data solutions.

## Description

* Design, develop, and maintain scalable cloud-based data engineering solutions, including ETL/ELT pipelines, data integration processes, reports, and analytics workflows using technologies such as Azure Databricks, Azure Synapse Analytics, Azure Data Factory, and SQL.
 * Demonstrate expert knowledge of modern cloud architecture, data lakehouse design, and data warehousing best practices, evaluating technical design alternatives and their business and operational impacts.
 * Develop, optimize, and troubleshoot complex SQL, T-SQL, Spark SQL, and PySpark workloads, with a strong focus on performance tuning, scalability, reliability, and cost efficiency.
 * Design, code, test, tune, deploy, and document new and existing data solutions, including Databricks notebooks developed in Python, PySpark, Spark SQL, and Scala, as well as cloud-native applications, APIs, and data pipelines utilizing Git, CI/CD, and Azure DevOps best practices.
 * Manage the complete development lifecycle for complex, high-impact data initiatives, including requirements gathering, solution design, development, testing, deployment, production support, and continuous improvement.
 * Support and enable AI, machine learning, and Generative AI initiatives by developing curated datasets, feature engineering pipelines, and scalable data platforms that power advanced analytics and intelligent business solutions.
 * Stay current with emerging trends and technologies in cloud computing, data engineering, artificial intelligence, Databricks, Azure services, automation, and analytics, recommending innovative solutions that drive business value and operational excellence.
 * Collaborate effectively with business stakeholders, architects, developers, and leadership teams, leveraging exceptional verbal and written communication skills to translate business requirements into scalable technical solutions and communicate complex concepts to both technical and non-technical audiences.
 * Perform other functionally related duties and responsibilities as assigned.