Big Data Engineering Professional
6 days ago
Job Overview:
Zensar Technologies is seeking a highly skilled Data Engineer to join our team. As a key member of our engineering team, you will play a crucial role in designing and developing scalable data pipelines using Hadoop, Spark, and related technologies.
About the Role:
- Data Pipeline Development: Develop and maintain robust data pipelines that process and analyze large datasets, ensuring high-quality results and optimal performance.
- Big Data Systems: Work with Hadoop Ecosystem tools such as HDFS, Hive, HBase, and Pig to manage and optimize data storage, retrieval, and processing.
- ETL Design and Implementation: Build and optimize Extract, Transform, Load (ETL) workflows for high-volume data integration from various sources, utilizing tools like Apache Nifi and Talend.
- Performance Optimization: Analyze and tune the performance of large-scale data processing workflows and jobs in a distributed computing environment, leveraging your expertise in programming languages such as Java, Scala, or Python.
- Collaboration: Collaborate with cross-functional teams, including Data Scientists, Analysts, and Product Managers, to gather requirements and deliver optimal data solutions.
- Data Quality & Security: Ensure data integrity, quality, and security by implementing robust validation checks, monitoring, and logging mechanisms.
- Innovation: Stay updated with the latest trends in Big Data technologies and continuously improve processes and systems with innovative solutions.
Requirements:
- Experience: 3+ years of experience working with Big Data technologies, particularly within the Hadoop Ecosystem (HDFS, Hive, Spark, HBase, Pig, Flume, etc.).
- Programming Skills: Strong programming experience in Java, Scala, or Python for data processing.
- Big Data Tools: Hands-on experience with Apache Spark, Hive, HBase, YARN, MapReduce, Kafka, and Flume.
- ETL Frameworks: Experience in building ETL pipelines and working with tools like Apache Nifi, Talend, or similar.
- Data Modeling & Warehousing: Knowledge of data warehousing, data modeling, and SQL (experience with NoSQL databases is a plus).
- Cloud Experience: Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform and big data services like EMR, DataProc, etc.
- Data Integration: Experience integrating data from multiple sources and working with structured and unstructured data.
- Version Control & CI/CD: Familiarity with version control tools like Git and continuous integration/continuous deployment practices.
- Problem-Solving & Analytical Skills: Strong troubleshooting skills and ability to work on complex data problems in a fast-paced environment.
Salary Range: $120,000 - $160,000 per annum.
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