Data Engineer

Startek Pro Technologies is hiring a Data Engineer in Dallas, TX (onsite) to help build scalable data pipelines and architectures that power analytics and machine learning. This role centers on engineering high-quality, accessible data through robust ETL, data modeling, and distributed big data systems, while collaborating across teams to turn data needs into solutions on AWS, Azure Data Lake, or other public cloud services. The hourly compensation range is USD 45–55/hour.

What you’ll do

• Develop, implement, and optimize ETL pipelines to move and transform data from multiple sources into centralized data warehouses or data lakes.
• Design and maintain data models and schemas using dimensional modeling to support business intelligence and analytics needs.
• Manage large-scale data processing using Hadoop (including HDFS), Spark, Hive, and other distributed processing frameworks.
• Collaborate with cross-functional teams to understand data requirements and translate them into scalable solutions using cloud platforms such as AWS and Azure Data Lake.
• Integrate diverse datasets from SQL databases (including Microsoft SQL Server and Oracle), cloud databases, and linked data environments to form unified datasets.
• Write efficient SQL queries and automation scripts using Python or Bash to support analysis, troubleshooting, and data workflow reliability.
• Support the development of RESTful APIs to enable seamless data access and integration with external applications.
• Apply best practices for data management, security, and governance while maintaining high performance for data systems.

What you bring

• Proven experience designing and implementing data warehousing solutions using Informatica, Talend, or similar ETL platforms.
• Strong SQL skills across Microsoft SQL Server, Oracle, and cloud-based systems such as Azure Data Lake or similar platforms.
• Hands-on big data experience with the Hadoop ecosystem (including HDFS), Spark, Hive, and related frameworks.
• Ability to develop scalable ETL pipelines using Python, Shell scripting (Bash), or other scripting languages in an Agile environment.
• Familiarity with cloud computing platforms such as AWS or Azure Public Cloud for deploying and managing big data systems.
• Knowledge of data modeling principles, especially dimensional modeling, for building warehouses that support analytics.
• Experience with business intelligence tools such as Looker to translate complex datasets into insights.
• Strong analytical capability with the ability to troubleshoot issues quickly while maintaining high-quality data management standards.

Technologies you’ll work with

ETL, SQL, Python, Bash, RESTful APIs, Hadoop, Spark, Hive, HDFS, AWS, Azure Data Lake, Informatica, Talend, Microsoft SQL Server, Oracle, Looker, Azure Public Cloud, dimensional modeling.