Job Title:
Cyber Data Engineering Leader
This role will oversee the strategic development and execution of advanced analytics and machine learning initiatives to drive business growth and operational efficiency.
The Cyber Data Engineering Leader collaborates closely with cross-functional leaders to identify high-impact opportunities, transform data into actionable insights, and develop predictive models that inform decision-making.
* Lead the design, development, and deployment of data solutions for the global practice to support new product development, research and development, insights/thought leadership, and reporting.
* Manage complex projects with direct reporting to senior management, ensuring alignment with business objectives and delivering measurable impact on product development, operational efficiency, and data monetization.
* Act as lead and mentor for a global team of direct and indirect reports performing data engineering and related data services, including establishing best practices, code reviews, and quality assurance standards.
* Collaborate with cross-functional teams across the organization to optimize data collection, analysis, and monetization strategies.
* Define and implement reference architecture and data flow processes, ensuring efficient data management across organizational systems and transitions.
* Establish and enforce data governance, metadata management, and data quality standards to ensure data integrity, lineage, and compliance.
Requirements:
* Proven experience in leading data engineering and data science teams, with a strong understanding of advanced analytics and machine learning.
* Expertise in designing and implementing data solutions, including data pipelines and machine learning models.
* Excellent communication and interpersonal skills, with the ability to influence and engage stakeholders at all levels.
* Strong analytical and problem-solving skills, with a focus on delivering actionable insights and driving business performance.
What sets you apart:
* Experience with data governance, data quality assurance, and ethical AI practices.
* A track record of driving innovation by evaluating, developing, and integrating new datasets to develop new revenue-generating products.
* Knowledge of emerging data technologies and trends, with the ability to recommend tools and practices to enhance organizational data capabilities.
Why join our organization:
* We offer professional development opportunities, interesting work, and supportive leaders.
* We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients, and communities.
* Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.
At Marsh McLennan, we are 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, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, Traveller community, or any other characteristic protected by applicable law. We are an equal opportunities employer. We are committed to providing reasonable support to any candidate with a disability/health condition to allow them to fully participate in the recruitment process. We encourage candidates to contact us at reasonableaccommodations@mmc to discuss any specific needs.
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.
Key Responsibilities:
* Develop and execute data-driven solutions to drive business growth and operational efficiency.
* Collaborate with cross-functional teams to optimize data collection, analysis, and monetization strategies.
* Establish and enforce data governance, metadata management, and data quality standards to ensure data integrity, lineage, and compliance.