[Hiring] Manager, Data Aggregation & Distribution L2 Support @Parexel

Role Description

We are seeking a Manager for Data Aggregation & Distribution L2 Support to join our team. As a Manager for Data Aggregation & Distribution L2 Support, you will drive critical data operations that enable clinical research at scale. This position plays a key role in leading technical support teams, ensuring data pipeline reliability, maintaining regulatory compliance, and delivering exceptional service to internal and external stakeholders. You'll collaborate with cross-functional teams, establish best practices, and contribute to data platform excellence from strategy through execution.

Responsibilities include:

• Overseeing L2 support operations.
• Leading and developing high-performing teams.
• Driving continuous improvement across Azure, Databricks, Snowflake, Denodo, and Power BI environments.

You'll join a fast-paced, growth-oriented environment focused on making a meaningful impact through supporting data-driven clinical research, building technical excellence, and advancing data platform capabilities. With diverse teams and continuous learning opportunities, the Manager for Data Aggregation & Distribution L2 Support can explore career paths and expand skills across clinical research technology and data operations.

Key Responsibilities:

• Lead, manage, and develop a team of 14 L2 data support specialists, providing clear direction, coaching, and performance oversight to foster a high-performance culture.
• Oversee the triage, diagnosis, and resolution of data pipeline, ingestion, and distribution issues, acting as an escalation point for complex technical problems.
• Monitor support queue performance and service levels, ensuring timely issue resolution and maintaining agreed SLAs across all data platforms.
• Collaborate with internal stakeholders including platform data teams, data engineering, analytics, and business functions to identify requirements and resolve recurring issues.
• Identify opportunities to improve data support operations, pipeline reliability, and team efficiency through continuous process improvement and innovation.
• Maintain and enforce support procedures, runbooks, and escalation protocols while ensuring team adherence to IT procedures, quality standards, and data governance requirements.

Qualifications

• Strong people management and team leadership capability with a proven track record of building and developing high-performing teams.
• Experience with cloud data platforms including Azure, Databricks, Snowflake, and Denodo, with hands-on knowledge of data pipeline monitoring and troubleshooting.
• The ability to collaborate across teams and communicate clearly with both technical and non-technical audiences.
• A data-focused mindset with strong attention to detail, analytical problem-solving skills, and the ability to manage competing priorities under pressure.
• Comfort working with ITSM platforms (e.g., ServiceNow), ticketing systems, and modern cloud-based solutions.

Requirements

• Bachelor's degree in computer science, Information Systems, Data Engineering, or a related technical field (or equivalent work experience).
• 2-5 years of demonstrated experience managing technical support or data operations teams, preferably in an enterprise or CRO environment.
• Hands-on experience with cloud data platforms, preferably Azure, Databricks, Snowflake, and Denodo.
• Proven experience supporting or operating within Medallion Architecture-based Data Lake environments.
• Track record of leading and developing teams of 10 or more technical staff.
• Strong communication, organization, and problem-solving skills.

Preferred Qualifications

• Relevant cloud platform certifications (e.g., Microsoft Azure Data Engineer, Databricks Certified Associate).
• ITIL Foundation certification or equivalent service management qualification.
• Experience managing L2 support functions including escalation management and SLA ownership.
• Familiarity with GxP or regulated life sciences data environments.
• Experience with data governance and quality standards in enterprise environments.

Benefits

• Flexibility, growth, and creating space for people to do their best work.