Big Data Engineer || Phoenix, AZ (Day 1 Onsite) at Phoenix, Arizona, USA |
Email: [email protected] |
Hi, Hope you are doing great! We have an urgent requirement open fo r "Big Data Engineer " position with one of our CLIENT AT Phoenix,AZ(Day 1 Onsite) PLEASE MENTION VISA AND CURRENT LOCATION OF CONSUTANT WHILE SHARING Job Title: Big Data Engineer Location: Phoenix, AZ (Day 1 Onsite) Duration: Long-term Job Description We are seeking a highly skilled Big Data Engineer to join our team and contribute to building robust and scalable data solutions. The ideal candidate will have a strong foundation in data engineering principles and a proven track record of designing, developing, and implementing big data pipelines. Responsibilities: Design, develop, and maintain scalable data pipelines using Spark, SQL, and other big data technologies. Extract, transform, and load (ETL) data from various sources into data warehouses and data lakes. Optimize data pipelines for performance and efficiency. Develop and implement data quality checks and monitoring processes. Collaborate with data analysts and data scientists to understand data requirements and translate them into technical specifications. Troubleshoot and resolve data-related issues. Stay up to date with the latest big data technologies and trends. Qualifications: Bachelors degree in computer science, Engineering, or a related field. 3+ years of experience in big data engineering. Strong hands-on experience with Spark for data processing and analysis. Proficiency in SQL for data querying and manipulation. Experience with data warehousing and data lake concepts. Knowledge of Python or Scala programming languages is a plus. Experience with cloud platforms (AWS, GCP, Azure) is preferred. Strong problem-solving and analytical skills. Excellent communication and collaboration skills. Preferred Skills: Experience with data ingestion tools (Kafka, Flume). -- Keywords: rlang information technology Arizona Big Data Engineer || Phoenix, AZ (Day 1 Onsite) [email protected] |
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Fri Sep 13 01:10:00 UTC 2024 |