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About the Role
This is a hands-on technical leadership role where you will lead a squad of data engineers, build data models, write code, and present delivery plans to stakeholders. You will own technical delivery for priority initiatives within Marsh's Innovation & Data Office (IDO), adapting to evolving priorities while maintaining high engineering leadership standards. The role requires a blend of technical expertise and people leadership, focusing on driving outcomes rather than managing people in a traditional sense.
Responsibilities
- Lead a delivery squad of 4-8 data engineers (employees and contractors), setting technical direction, decomposing work, managing sprint-level execution, and ensuring squad shipments.
- Write code, build pipelines, and debug production issues using SQL, Python, and Spark.
- Design maintainable data solutions, including data models, medallion architectures, and ingestion contracts, considering schema evolution, data quality, idempotency, and lineage.
- Collaborate with Engagement Leads and business stakeholders to understand needs, translate business problems into data solutions, and communicate technical trade-offs.
- Drive engineering standards, including CI/CD, version control, testing, code review, and documentation, to improve developer experience and operational excellence.
- Operate on a modern stack including Databricks (Unity Catalog, Delta Lake, Spark, medallion architecture) on AWS and Azure, utilizing infrastructure-as-code, Git-based workflows, and pipeline orchestration tools.
Requirements
- 5+ years of hands-on data engineering experience, with some experience leading or mentoring other engineers.
- Strong proficiency in SQL, Python, and Spark, used recently and regularly.
- Real experience with cloud data platforms (Databricks strongly preferred; Snowflake, Synapse, or similar accepted) on AWS, Azure, or GCP.
- Demonstrated ability to lead a mixed team of employees and contractors: setting expectations, managing performance, building cohesion across employment types.
- Fluency with modern engineering practices: Git, CI/CD, automated testing, infrastructure-as-code, DataOps.
- Intellectual curiosity about the business domain.
- Clear communication skills; ability to explain technical trade-offs to business leaders and business requirements to engineers.
Skills
- SQL
- Python
- Spark
- Databricks
- Unity Catalog
- Delta Lake
- Medallion architecture
- AWS
- Azure
- GCP
- Git
- CI/CD
- Automated testing
- Infrastructure-as-code
- DataOps
- dbt
- Data governance
- Lineage
- Access controls
- Metadata management
- Data quality frameworks
- Document or unstructured data ingestion pipelines
- LLM-based tooling
- AI-assisted development
- Analytics engineering
Location
- Mexico City/MX
- Toronto/CA
Work Type
- Hybrid
Experience Level
- 5+ years of hands-on data engineering experience
- Some time leading or mentoring other engineers
Benefits
- Flexibility of working remotely
- Collaboration, connections and professional development benefits of working together in the office
About the Company
- Marsh is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries.
- Marsh has annual revenue of over $27 billion and more than 95,000 colleagues.
- Marsh helps build the confidence to thrive through the power of perspective.
- For more information, visit marsh.com, or follow us on LinkedIn and X.
Equal Opportunity
- Marsh is committed to creating 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, or any other characteristic protected by applicable law.
- All Marsh 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.