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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Specialist - Data Engineering - **Company:** LTM Inc - **Location:** Irving, TX, United States - **Experience:** Expert - **Salary:** $83,912.0 - $128,080.0 - **Contract:** Internship / Graduate position - **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Cloud Database, Computer Programming, Databases, Continuous Integration, Directed Acyclic Graph (Directed Graphs), Information Engineering, Data Files, Data Infrastructure, Data Integration, Data Transformation, Dataspaces, Data Systems, Data Warehousing, Relational Databases, Apache Hadoop, Apache HBase, Apache Hive, Python (Programming Language), MongoDB, NoSQL, Performance Tuning, Cloud Services, Ansible, Simple Data Format, Workflow Management Systems, Parquet, Google Cloud, Apache Spark, Git, Data Lakes, Ansi Sql, Pyspark, Deployment Automation, Cassandra, Avro, Star Schema, Data Management, Data Delivery, Software Coding, Data Pipelines, Amazon Elastic Mapreduce (EMR), Databricks - **Published:** November 5, 2026 - **Apply:** https://www.careerbuilder.com/job-details/specialist-data-engineering-irving-tx--7da9a11b-7ed3-4f97-9317-183a70f4e275 ## About the Role English Language, Facebook, LinkedIn, Data Sets, Apache Hive, Business Intelligence, Data Management, Apache Spark, Building Design, Cloud Computing, * Big Data Frameworks Expertise Demonstrated high proficiency in Apache Spark architecture including a deep understanding of drivers executors and Directed Acyclic Graphs DAGs * Advanced Programming Exceptional coding skills in Python and extensive experience with the PySpark API for developing intricate data transformations and processing logic * Querying Schema Management Strong command of HiveQL and ANSI SQL coupled with expertise in data partitioning techniques and effective schema definition * Optimized Storage Formats Indepth understanding and practical experience with optimized big data storage file formats such as Parquet ORC and Avro * Cloud Ecosystem Development Handson development experience utilizing cloudnative big data utilities eg AWS EMR Azure Databricks within major cloud platforms * Data Warehousing Fundamentals Solid foundation in Dimensional Data Modeling including Star and Snowflake schemas and practical experience with Data Lakes concepts and implementation * Preferred Qualifications * CICD DevOps Automation Experience with Continuous IntegrationContinuous Deployment CICD practices and automation tools like Git Jenkins or Ansible * NoSQL Database Integration Exposure to and experience with NoSQL databases such as HBase Cassandra or MongoDB * Professional Cloud Certifications Relevant professional cloud certifications eg AWS Certified Data Engineer Microsoft Certified Azure Data Engineer Associate are highly valued Skills Mandatory Skills : Apache Spark, Big Data Hadoop Ecosystem, Python for DATA ## Description * We are seeking a highly skilled and motivated Data Engineer to play a pivotal role in designing building and optimizing our next generation scalable data pipelines This position requires expertise in processing massive datasets using cutting-edge technologies like Apache Spark PySpark and Hive within a dynamic cloud environment Your primary objective will be to ensure the utmost data reliability speed and efficiency providing a robust foundation for downstream business intelligence and advanced analytics initiatives * Key Responsibilities * Data Pipeline Development Maintenance Design build and maintain highly scalable and efficient ETLELT data pipelines utilizing PySpark and Spark SQL for complex data transformations * Cloud Data Infrastructure Management Deploy manage and scale critical data infrastructure components on leading cloud platforms such as Amazon Web Services AWS eg EMR Glue Microsoft Azure eg Databricks Synapse or Google Cloud Platform GCP * Data Warehousing Storage Optimization Strategically manage data layout partitioning and indexing within Apache Hive and various cloud data lake solutions to optimize performance and accessibility * Performance Tuning Optimization Proactively identify and resolve performance bottlenecks in Spark jobs leveraging Spark UI for indepth analysis effectively managing data skewness and optimizing memory utilization * Diverse Data Integration Develop robust solutions for ingesting highvolume and diverse datasets from both structured relational databases and unstructured flat files into our data ecosystem * Automated Workflow Orchestration Implement and manage automated data workflows using industrystandard scheduling tools like Apache Airflow or platformnative schedulers ensuring timely and reliable data delivery * Strategic Collaboration Partner closely with data scientists business analysts and crossfunctional enterprise teams to translate complex business requirements into technically sound and efficient data solutions