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Strong consulting brand, metro location, generalist data-engineer role with broad skillset drives high competition.
Core data-engineering skills transfer across industries, though client-facing consulting experience moderately increases sensitivity.
Mandatory Python, cloud and big-data skills plus CI/CD requirements make shortlisting moderately strict.
Develop, deploy, and monitor high-performance data engineering applications that support large-scale machine learning and advanced analytics frameworks.
Collaborate directly with Oliver Wyman consulting teams and clients to understand business challenges and deliver tailored data solutions and pipelines.
Lead development and documentation of data engineering assets, ensuring operational excellence and best practices in code quality and architecture guidance.
Bachelor's or master’s degree in Computer Science, Informatics, Data Science, or related quantitative discipline from a top academic program.
Experience designing and deploying cloud-native data applications using AWS, Azure, or Google Cloud Platform.
Proficiency in Python (mandatory) and strong SQL skills with experience on relational databases like MySQL, PostgreSQL, or Oracle.
Work Experience Required: 0-8 years in data engineering roles with familiarity in big data tools like PySpark, Databricks, Snowflake, and CI/CD pipeline integration.
Ability to work independently and prioritize workload in fast-paced environments while collaborating effectively with cross-functional teams including consulting partners.
Experience mentoring junior engineers on advanced data engineering concepts and quality assurance practices, aligned with Senior or Lead Engineer levels.
Strong pragmatic problem solver with experience deploying production-grade data pipelines and integrating emerging data engineering frameworks and tools.