Data EngineerEXL • Dallas, Texas, United States
Data Engineer
EXL • Dallas, Texas, United States
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job_description.job_card.job_descriptionDevelop scalable ETL pipelines using PySpark, Hive, and Python. Build reusable frameworks for data ingestion, transformation, and aggregation. Optimize job performance through query tuning, resource management, and parallelization. Maintain and promote code across DEV, QA, UAT, and PROD environments. Develop and support CI / CD pipelines using Jenkins and uDeploy for automated deployments. Perform environment upgrades, patching, and dependency management aligned with release schedules. Execute Linux administration tasks including performance tuning, disk management, and scripting (Bash / Python). Troubleshoot cluster-level issues including node failures, job errors, and distributed system anomalies. Drive incident resolution and change execution using ServiceNow workflows. Conduct root cause analysis (RCA) for critical issues and implement preventive solutions. Ensure compliance with ITIL processes for change, incident, and problem management. Partner with data engineers, developers, DevOps teams, and business analysts to ensure operational excellence. Mentor junior engineers and contribute to technical leadership across the Big Data ecosystem. Document operational procedures, troubleshooting guides, and architectural decisions for internal knowledge sharing. Bachelor’s degree in Computer Science, Information Technology, or related field. 8+ years of experience in Big Data engineering and DevOps practices. Advanced proficiency in HDFS, Hive, Impala, PySpark, Python, and Linux. Proven experience with CI / CD tools such as Jenkins and uDeploy. Strong understanding of ETL development, orchestration, and performance optimization. Experience with ServiceNow for incident / change / problem management. Excellent analytical, troubleshooting, and communication skills. Exposure to cloud-based Big Data platforms (AWS EMR). Familiarity with containerization (Docker, Kubernetes) and infrastructure automation tools (Ansible, Terraform).
Position : Data Engineer
Location : Location : Hybrid (3 days onsite, 2 days’ work from Home) Pittsburgh / Cleveland / Dallas / Phoenix
Experience : 8+ Years
Education : Bachelor’s degree
Key Responsibilities :
Big Data Platform Operations
- Design, manage, and optimize HDFS directories, tables, and partitioning strategies.
- Implement and enforce data retention and lifecycle policies across large datasets.
- Administer Hive and Impala environments, ensuring high availability, performance tuning, and security compliance.
ETL Development & Data Engineering
DevOps & Environment Management
Linux & Infrastructure Operations
Change & Incident Management
Collaboration & Technical Leadership
Required Qualifications :
Nice to Have :
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