| Tomorrow Interview (Need Python, Spark & Databricks) || Data Engineer Lead || NYC, NY (Hybrid) at NYC, New York, USA |
| Email: [email protected] |
| From: Rahul Kumar, SPAR Information Systems [email protected] Reply to: [email protected] Hello Folks, (Must have exp with Python, Spark & Databricks) & Prefer only from EST profiles Hope you all are doing good. Please go through the Job description and let me know your interest. Title: Data Engineer Lead Work Location: NYC, NY (Onsite/ Hybrid) Duration: Long Term Contract Mandatory Skill-Lead Python & Spark. Exp in databricks 5 year in data engineering and building pipelines. Strong coder, skills in Python and SQL Job Description: High-Performance Culture: Be a key player in our high-performing team, surrounded by intellectual minds eager to collaborate and learn from each other. Key Contributions: Be a key contributor on one of top-priority initiatives, backed by strong senior management support. The platform is already making waves, and now it & your chance to steer it to new heights. Visible Impact: Make your mark by driving the platform forward, contributing to its success and widespread adoption. What We are Looking For: Experienced Data Engineer: We need an experienced data engineer with a proven track record of driving product success from an engineering perspective. We are looking for someone who has strong experience in building scalable and reliable data pipelines using Databricks and Spark. You will be working with various data sources and formats, and transforming them into valuable insights for our business Cultural Fit: Join our collaborative, respectful, and intellectually curious team. We are persistent problem solvers, communicative, results-driven, and positivebringing accountability and ownership to everything we do. Your Role: Holistic Learning: Dive into the intricacies of our platform, mastering its ins and outs. Strategic Contributions: Design, develop, and maintain data pipelines using Databricks and Spark, and other cloud technologies as needed Hands-On Contribution: Tackle challenging tasks as a hands-on contributor, ensuring a seamless transition between various facets of this dynamic role throughout the workday. Optimize data pipelines for performance, scalability, and reliability Ensure data quality and integrity throughout the data lifecycle Collaborate with data scientists, analysts, and other stakeholders to understand and meet their data needs Troubleshoot and resolve data-related issues, and provide root cause analysis and recommendations Document data pipeline specifications, requirements, and enhancements, and communicate them effectively to the team and management Create new data validation methods and data analysis tools, and share best practices and learnings with the data engineering community Implement ETL processes and data warehouse solutions, and ensure compliance with data governance and security policies NY-based (min. 2 days in office each week: Tuesday plus one other day) Required Qualifications Strong background in Computer Science fundamentals including: algorithms, data structures, computational complexity, distributed computing 5+ years of experience in data engineering, preferably with Databricks and Spark Proficient in SQL and Python, and familiar with Java or Scala Experience with cloud platforms, preferably Azure Experience with data warehouse and data lake concepts and architectures Experience with data integration and ETL tools, preferably Azure Data Factory Strong analytical and problem-solving skills Excellent communication and teamwork skills Nice-to-Have Experience with big data technologies, such as Kafka, Hadoop, Hive, etc. Experience with data visualization and reporting tools, preferably Tableau Thanks & Regards, Rahul Kumar Sr. Technical Recruiter SPAR Information Systems (a E-verify Company) Email : [email protected] Keywords: information technology golang New York Tomorrow Interview (Need Python, Spark & Databricks) || Data Engineer Lead || NYC, NY (Hybrid) [email protected] |
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| Wed May 22 18:48:00 UTC 2024 |