Senior Specialist - Data Engineering
Marsh & McLennan Companies27 days ago
Brussels, Belgium +9 moreSenior
Responsibilities
- Lead, coach, and mentor engineers while providing hands-on technical leadership.
- Design, build, and maintain scalable, resilient, secure platform capabilities using AWS and Databricks.
- Develop reusable platform services, patterns, and frameworks for data and engineering teams.
- Oversee data pipelines, ingestion frameworks, transformation workflows, and distributed processing solutions.
- Embed data quality, observability, lineage, security, compliance, and governance into platform solutions.
- Use AWS services including S3, Lambda, Glue, Step Functions, RDS, IAM, and CloudWatch.
- Drive automation, infrastructure-as-code, CI/CD, monitoring, alerting, logging, incident response, and cost optimization.
- Partner with product, architecture, security, business, and domain teams to translate requirements into engineering solutions.
- Improve developer experience, release processes, testing strategies, and operational maturity.
- Set engineering standards and promote continuous improvement across the team and platform.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related discipline, or equivalent practical experience.
- Significant experience in software engineering, platform engineering, or data engineering, including time in a senior or lead capacity.
- Strong hands-on experience designing and delivering AWS solutions.
- Strong experience with Databricks or similar data lakehouse technologies in enterprise data or platform environments.
- Proven experience building and supporting scalable data pipelines, distributed processing workloads, and cloud-native platforms.
- Experience leading engineers and driving technical delivery across cross-functional teams.
- Experience with platform automation, CI/CD pipelines, infrastructure as code, and governed enterprise environments.
- Strong programming capability in Python and SQL, with a good understanding of Spark and distributed data processing.
- Experience with data architecture, data modeling, lakehouse principles, observability, and workflow orchestration.
- Familiarity with Terraform, CloudFormation, Git, containerization, and related engineering tooling.
- Strong leadership, stakeholder management, communication, problem-solving, and analytical skills.
- Preferred experience includes financial services or other regulated environments, shared platforms, data governance, metadata, lineage, access control, AWS certifications, and Databricks certification.
Benefits
- Hybrid work with flexibility to work remotely and collaborate in the office; colleagues are expected to work from their local office or onsite with clients at least three days per week.
- Office-based teams will identify at least one weekly anchor day for the full team to work together in person.
- Marsh provides a diverse, inclusive, and flexible work environment and reasonable accommodations as required by applicable law.
About Marsh & McLennan Companies
Marsh McLennan is a global professional services firm providing risk, insurance and reinsurance brokerage, health, wealth, and management consulting to corporations, governments, and nonprofits. It operates through Marsh, Guy Carpenter, Mercer, and Oliver Wyman, earning fees and commissions for advisory, analytics, and placement services. Founded in 1905 and headquartered in New York, it is publicly traded on the NYSE under the ticker MMC.