Data Engineer |Databricks | 12 month agency contract

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Описание

Key Responsibilities · Develop and maintain data processing solutions using Databricks and Python. · Design and implement real-time data processing pipelines using Apache Spark Structured Streaming. · Develop efficient and scalable data processing logic using strong Python programming fundamentals and data structures. · Troubleshoot and optimize streaming jobs and data processing workflows. · Work with large volumes of data and ensure reliable, scalable, and efficient processing. · Monitor and resolve issues related to streaming pipelines and Databricks workloads. · Collaborate with data engineers, technical teams,and stakeholders to understand requirements and deliver effective solutions. · Follow best practices for code quality,performance, maintainability, and operational support. · Participate in troubleshooting, debugging, and performance optimization of data pipelines. Required Skills & Experience: · 5–10 years of overall experience in data engineering / data development. · Strong hands-on experience with Databricks. · Strong experience with ApacheSpark Structured Streaming. · Strong Pythonprogramming skills with a good understanding of: · Experience developing and troubleshooting batch and/or streaming data pipelines. · Good understanding of data processing concepts anddistributed computing. · Strong problem-solving and analytical skills. · Ability to work independently as well as collaboratively with technical teams. Interested candidates who wish to apply for the above position please click the "Apply Now' button and send your resume to: We regret that only shortlisted candidates will be notified. PERSOL Singapore Pte Ltd EA License No: 01C4394| Saravanan| Reg No: 01C4394 By sending us your personal data and curriculum vitae (CV), you are deemed to consent to PERSOL Singapore Pte Ltd and its affiliates to collect, use, and disclose your personal data for the purposes set out in the Privacy Policy available at [link] You acknowledge that you have read, understood, and agree with the Privacy Policy.

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