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Urgent! Softpath Technologies - Senior Big Data Engineer - Hive & Unix Scripting Job | Softpath Technologies LLC

Softpath Technologies Senior Big Data Engineer Hive & Unix Scripting



Job description

<p><p><b>Description : </b></p><br/><p><b>Job Title : </b>Senior Big Data Engineer Hive & Unix Scripting</p><br/><p><b>Location : </b>Pune / Hyderabad, India</p><br/><p><b>Experience :</b>6 - 8 Years</p><br/><p><b>Job Summary : </b><br/><br/>We are looking for an experienced Big Data Engineer with strong expertise in Hive, Unix/Linux scripting, and data pipeline development.

The ideal candidate will be responsible for designing, developing, and maintaining large-scale data solutions on Hadoop ecosystems, optimizing Hive queries, automating workflows, and ensuring the reliability and scalability of data systems.</p><br/><p>This role requires deep technical knowledge of Big Data technologies, strong analytical and scripting skills, and the ability to work closely with cross-functional teams including Data Architects, Analysts, and Business Stakeholders.</p><br/><p><b>Key Responsibilities : </b></p><br/><p>- Design, develop, and optimize Hive-based data models, queries, and tables for analytical and reporting use cases.</p><br/><p>- Develop and maintain Unix/Linux shell scripts for workflow automation, data ingestion, and monitoring.</p><br/><p>- Manage and enhance ETL pipelines across various data sources and sinks (HDFS, Hive, Sqoop, Spark, etc.).</p><br/><p>- Implement data quality checks, validations, and performance tuning for efficient data processing.</p><br/><p>- Work closely with Data Architects to design scalable data lake and warehouse architectures.</p><br/><p>- Monitor data jobs, troubleshoot failures, and ensure SLA adherence for data availability.</p><br/><p>- Collaborate with Analytics and BI teams to deliver clean, reliable datasets.</p><br/><p>- Contribute to migration or modernization projects, including moving on-prem Big Data workloads to cloud platforms (AWS/Azure/GCP).</p><br/><p>- Document design specifications, job flows, and operational procedures.</p><br/><p>- Stay up to date with the latest Big Data tools and best practices, recommending process improvements.</p><br/><p><b>Required Technical Skills : </b></p><br/><p>- <b>Big Data Ecosystem : </b> Strong experience with Hive, Hadoop (HDFS, YARN), and MapReduce.</p><br/><p>- <b>Scripting : </b> Advanced hands-on experience with Unix/Linux shell scripting (bash, ksh, etc.) for automation.</p><br/><p>- <b>Data Processing Tools : </b> Experience with Spark, Sqoop, Impala, or Pig is an added advantage.</p><br/><p>- <b>ETL Development : </b> Solid understanding of data ingestion, transformation, and orchestration frameworks.</p><br/><p>- <b>Performance Optimization : </b> Proven ability to tune Hive queries, partition strategies, and optimize joins and aggregations.</p><br/><p>- <b>Version Control : </b> Familiarity with Git, Bitbucket, or similar tools.</p><br/><p>- <b>Scheduling Tools : </b> Experience with Oozie, Airflow, or Control-M.</p><br/><p>- <b>Cloud Platforms (Optional) : </b> Exposure to AWS EMR, Azure Data Lake, or GCP Dataproc is a plus.</p><br/><p><b>Preferred Qualifications : </b></p><br/><p>- Bachelors or Masters degree in Computer Science, Information Technology, or related field.</p><br/><p>- Strong understanding of data warehousing concepts, data modeling, and SQL optimization.</p><br/><p>- Experience in data security, lineage, and governance practices.</p><br/><p>- Familiarity with Python or PySpark scripting for data manipulation.</p><br/><p>- Excellent problem-solving and analytical skills.</p><br/><p>- Strong communication skills and ability to work in an agile, team-oriented environment.</p><br/><p><b>Soft Skills : </b></p><br/><p>- Strong analytical and debugging mindset.</p><br/><p>- Excellent verbal and written communication.</p><br/><p>- Ability to work independently with minimal supervision.</p><br/><p>- Collaborative attitude and eagerness to learn emerging technologies.</p><br/></p> (ref:hirist.tech)


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