Data Engineer

Location: Dallas TX, Pittsburgh PA , Cleveland OH Work Mode: Hybrid Experience: 6 + Years Job Summary: We are seeking a highly skilled Data Engineer to support our big data infrastructure and ETL workflows. The ideal candidate will have strong expertise in Hive, Python, PySpark, Spark, and Scala, with a deep understanding of on-premises data platforms. You will be responsible for designing, developing, and optimizing data pipelines and workflows in a large-scale enterprise environment. Key Responsibilities: Design, develop, and maintain scalable ETL pipelines using Hadoop ecosystem tools. Develop data transformation logic using PySpark, Spark, Scala, and Python. Work with Hive for querying and managing large datasets. Optimize performance of ETL jobs and big data processes on an on-premises infrastructure. Collaborate with data engineers, analysts, and stakeholders to understand business requirements. Monitor and troubleshoot data workflows and ensure data quality and consistency. Implement best practices for code management, version control, and automation. Required Skills: Strong hands-on experience with Hadoop ecosystem (especially Hive, HDFS, YARN, etc.). Proficiency in PySpark and Spark for large-scale data processing. Solid programming skills in Python and Scala. Proven experience with on-premises big data architecture and deployment. Familiarity with ETL concepts, data warehousing, and performance tuning. Experience with job schedulers (e.g., Oozie, Airflow, etc.) is a plus. Ability to work independently and in a team-oriented environment. Seniority level

Seniority level

Mid-Senior level Employment type

Employment type

Full-time Job function

Job function

Engineering, Information Technology, and Analyst Industries

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