Job Description
Company:Oliver WymanDescription:
- Lead the overall architecture of data warehouse, including implementation of data models, ETL/ ELT processes and reporting frameworks, ensuring the architecture aligns with best industry practices and organization standards.
- Lead the design and implementation of processes to ingest data from various sources into the Databricks Lakehouse platform. Ensure platform performance and scalability.
- Oversee the development, maintenance, and optimization of data models and ETL pipelines that support the Medallion Architecture (Bronze, Silver, Gold layers) to enhance data processing efficiency and facilitate data transformation.
- Utilize Databricks to integrate, consolidate, and cleanse data, ensuring accuracy and readiness for analysis, while leveraging Delta Lake for versioned data management.
- Implement and manage Unity Catalog for centralized data governance, ensuring proper data access, security, and compliance with organizational policies and regulations.
- Collaborate with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility, and fostering data-driven decision making across the organization.
- Collaborate with business analysts, data scientists, and stakeholders to understand their data requirements and deliver tailored solutions that leverage the capabilities of the Databricks Lakehouse platform.
- Promote available data and analytics capabilities to business stakeholders, educating them on how to effectively leverage these tools and the Medallion Architecture for their analytical needs.
- Lead the migration of existing ETL processes from Informatica IICS and SSIS to cloud-based data pipelines within the Databricks environment, ensuring minimal disruption and maximum efficiency.
- Act as a technical lead during sprints, providing guidance and support to team members, and ensuring adherence to best practices in data engineering.
- Engage with clients and stakeholders to support architectural designs, address technical queries, and provide strategic guidance on utilizing the Databricks Lakehouse platform effectively.
- Demonstrate excellent problem-solving skills, with an ability to see and solve issues before they affect business productivity.
- Demonstrate thought leadership by contributing to the development of best practices, standards, and documentation for data engineering processes within the organization.
- Participate in all aspects of the software development lifecycle for AWS solutions, including planning, requirements, development, testing, and quality assurance
- Stay updated on industry trends and emerging technologies in data engineering, particularly those related to Databricks, cloud data solutions, and ETL migration strategies, continuously enhancing your skills and knowledge.
Marsh McLennan (NYSE: MMC) is a global leader in risk, strategy and people, advising clients in 130 countries across four businesses: Marsh, Guy Carpenter, Mercer and Oliver Wyman. With annual revenue of $24 billion and more than 90,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit marshmclennan.com, or follow on LinkedIn and X.Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law.Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.
