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Specialist
Specialist-March 2024
New York
Mar 28, 2026
About Specialist

  McKinsey & Company Inc. US is seeking a Specialist in New York, NY. Conduct business analysis and collect business requirements to translate them into Digital Solution leveraging best practices. Build physical data models to link data schema, modeling choices and business considerations. Design and implement data Extraction, Transformation, and Loading (ETL) pipeline leveraging modern data engineering architecture patterns. Implement robust and scalable big data engineering and analytics solutions using distributed programming and big data technologies like Hadoop, MapReduce and Spark. Apply statistical and machine learning methodologies to identify trend, pattern, anomality and commonality from various data sources. Develop and deliver automated reports and advanced visualization solutions using various business intelligence tools like Tableau and PowerBI. Architect, develop and deploy end-to-end data solutions on clients’ cloud platform, leveraging cloud services provided by Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP) etc. Define digital solution architecture and manage prioritization of features working with Agile development teams. Telecommuting permitted.Qualified applicants for this position must possess a Master’s degree in Analytics, Data Science, Statistics, or related field, or foreign degree equivalent. Qualified applicants for this position must have a minimum 2 years of experience developing data analytics solutions. Experience must include the following: Programming languages: Python, SQL, pySpark, Scala, R; Big data technologies: Hadoop, MapReduce, Hive, Spark, Kafka; Database technologies: Microsoft SQL, Teradata, Oracle; Business Intelligence tools: Tableau, JMP. Salary range: $192,000 - $208,000 / year. Email your resume to [email protected] & refer to Job # 7589339. Worksite: 3 World Trade Center, 175 Greenwich Street, NY NY 10007

  Minimum Salary: 192,000Maximum Salary: 208,000Salary Unit: Yearly

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