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# Senior Data Engineer

- **Company:** Tiger Analytics
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Big Data, Data Validation, Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Systems, Database Queries, Software Debugging, Distributed Computing Environment, Apache Hadoop, Python (Programming Language), Performance Tuning, Scala (Programming Language), Software Deployment, Software Engineering, Unstructured Data, Data Processing, Data Ingestion, Apache Spark, Data Management, Software Coding, Software Version Control, Data Pipelines, Databricks, Control M
- **Published:** October 8, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=1bbb65ba22ee36a9

## About the Role

+ 8+ years of overall Data Engineering experience.
 + Strong hands-on experience with Databricks and Apache Spark.
 + Proficiency in Python and Scala for data processing and application development.
 + Hands-on experience with Hadoop and big data technologies.
 + Experience with Control-M for batch scheduling, job monitoring, workflow orchestration, and dependency management.
 + Strong understanding of ETL/ELT processes, data transformations, and distributed data processing.
 + Experience in performance tuning, debugging, troubleshooting, and production support.
 + Strong SQL skills and understanding of data management concepts.
 + Excellent analytical, problem-solving, and collaboration skills.

## Description

We are seeking a Senior Data Engineer to join our advanced analytics and AI team supporting some of our large enterprise clients. In this role, you will be responsible for designing, developing, and maintaining scalable data pipelines, processing large datasets, and managing scheduled data workflows to support enterprise data engineering initiatives., * Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, Python, and Scala.

 * Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources.
 * Work with Hadoop and its ecosystem to process and manage large volumes of structured and unstructured data.
 * Develop, troubleshoot, and optimize Spark applications to improve performance, scalability, and reliability.
 * Use Control-M to schedule, monitor, and manage batch jobs, workflow dependencies, and data processing pipelines.
 * Troubleshoot job failures, resolve data pipeline issues, and ensure timely completion of scheduled workloads.
 * Implement data validation, error handling, and quality checks to ensure data accuracy and consistency.
 * Collaborate with data architects, analysts, and cross-functional teams to understand requirements and deliver reliable data solutions.
 * Follow coding standards, testing practices, version control, and deployment procedures.
 * Support production deployments, incident resolution, and ongoing maintenance of data engineering solutions.