Senior Manager - Data RunOps Support

Key Skills

Java Programming, Analytical and Problem solving, Management, Python Programming, SQL, DevOps, Machine learning techniques, Tableau, Amazon RedShift, Amazon EMR, Amazon Elastic Compute Cloud-EC2, Talend, Databricks, Amazon Simple Storage Service (S3), Data Engineering, Data Architecture

Job Description

McDonald’s is hiring for a Data RunOps Support Manager role. This role will be responsible for hands-on operational support, planning, technical management, and ultimately execution of production support and maintenance activities. This role requires technical hands on work with systems, excellent project and product management skills.

You will work with Data Domain teams (Customer, Restaurant, Supply Chain, and Sales Transactions), to identify, troubleshoot and implement reliability improvements across data-pipeline applications, infrastructure, monitoring and remediation. There is a significant consultant team (~60 of onshore and offshore), and this role will work with cross functional teams including and not limited to Data Architecture, Data Management, Data Movement and business stakeholders.

Success in this role requires software engineering and support management experience, and some work with cloud technologies.

What you will be doing:

• Stakeholder management across business, Product Owners, Enhancement and core RunOps team members
• Ensure and maintain high customer satisfaction scores (95+%) by providing world-class operational services with timely and accurate responses
• Troubleshoot and resolve escalations from users; communicate technical product issues, needs and solutions to Product Development teams and leadership
• Collaborating with data architecture, data management, and data domain teams
• Be on top of major incidents, statistics on run utilization, and service requests, to identify reliability and quality improvement opportunities
• Collaborating with other teams, while maintaining a longer-term, engineering oriented view on improvements
• Contributing to the improved operations of an extremely sophisticated data ecosystem, including 35+ applications, and 70M+ daily transactions across critical domains including Customer, Restaurant, Supply Chain, and Sales
• Ensuring the feedback loop remains tight, between any incidents, and five-why’s root cause improvements on how to prevent them from reoccurring
• Assisting in driving Operational Data Quality (DQ) efforts – including bridging operations, DQ checks, and roles & responsibilities for product teams vs. incident response
• Assisting in bringing SRE (Service/Site Reliability engineering ) concepts to life, for Data & Analytics services and platform
• Assisting integrate AIOps, MLOps, and other Machine Learning powered sophisticated methodologies into the platform
• Assisting in structural upgrades in the overall way our systems operate, across monitoring, maintenance, automation & architectural changes. This work is done in partnership with other teams doing aspects of tool & application building
• Assisting in engineering improvements and automation, creating an automation-first SRE/DevOps culture.

Additional considerations

• You must be sensitive to customer needs, be able to manage process, and have the engineering background to help champion structural improvements
• While this role is not part of a 24x7 shift rotation, you are expected to intermittently join calls at off-hours, if something urgent or unexpected occurs in production, for an area you are engaged with
• Able to perform under high pressure situations, with reasonable ‘client hands’ – our team serves the needs of the core of McDonald’s global data, and analytics platform capabilities.

Qualifications

• Must have received or be willing to receive the COVID-19 vaccination by date of hire to be considered. Proof of vaccination required.
• 5+ years relevant work experience in a technical support management role – such as data engineering, applications engineering, or engineering support
• Experience with Cloud ecosystem (preferably AWS). Components of overall technology stack include: EC2, EMR, BigData, S3, Talend, Python, Redshift, Tableau, Databrick and more
• Ability to think structurally on engineering upgrades - able to engage, challenge, and constructively elevate the thinking of your team
• Bachelor’s degree in Computer Science, Information Technology or a related degree
• Strong problem-solving skills and ability to focus on details as well as the big picture
• A self-starter with a strong bias for action; Proven track record of “getting things done