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# Data & Infrastructure Lead (Managing Supervisor)

- **Company:** FleishmanHillard, Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $78,920.0 - $117,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Information Engineering, Data Infrastructure, Data Visualization, Database Queries, Google Analytics, Python (Programming Language), Machine Learning, Power BI, Tensorflow, Software Deployment, SQL Databases, Tableau (Software), Web Analytics, Scripting, Llamaindex, Build Management, Containerization, Looker Analytics, Automation Anywhere, Docker
- **Published:** October 21, 2026
- **Apply:** https://www.manhattanjobs.com/job.asp?id=3462147453&tx=FL104LFU&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Experience: 5-8+ years of experience in digital marketing analytics, data engineering, or data infrastructure management (with prior experience leading project streams or small teams).
 * Technical Command: Hands-on command of standard marketing intelligence platforms (e.g., Brandwatch, Netbase Quid, Talkwalker, Sprinklr) and scripting languages (Python, SQL, or R) for automation.
 * Data Visualization & Delivery: Experience constructing executive dashboards and distilling complex datasets into clear narratives and visual scorecards.
 * Project Management: Track record of managing project execution, technical scopes, and deliverables in an agency or fast-paced consulting environment.
 * Communication: Clear verbal and written skills to collaborate across technical engineers and cross-functional account teams.

Nice-to-Haves:

 * Experience with cloud platforms (GCP, AWS) and sandbox configurations.
 * Familiarity with AI/ML frameworks (LangChain, LlamaIndex) or containerization tools (Docker).
 * Proficiency in BI tools (Tableau, Google Looker Studio, Power BI) and web analytics (Google Analytics)
 * Exposure to media monitoring platforms (Onclusive, Zignal, Newswhip) and consumer research tools (YouGov, GlobalWebIndex).

## Description

Methods+Mastery has an immediate opening for a skilled, hands-on Data & Infrastructure Lead (Managing Supervisor). Reporting to the Vice President, Director of Data & Infrastructure, you will serve as a lead execution partner and technical bridge connecting our data engineers, analysts, and Fortune 50 clients.

In this role, you will take ownership of day-to-day data environment builds, automate reporting workflows, and translate technical infrastructure and AI initiatives into clear, actionable business insights for client stakeholders. You will play a central role in scaling our intelligence offerings, maintaining pipeline accuracy, and driving technical enablement across analyst teams., 1. Client Communication & Project Delivery

 * Technical Translation: Assist in translating complex pipeline, automation, and AI workflows into actionable business outcomes for non-technical client contacts.
 * Project Execution: Lead day-to-day project delivery across client briefs, enforcing project timelines, scopes, and quality controls for data methodologies.
 * Consultative Support: Partner with senior leadership to deliver data maturity assessments and present regularly scheduled business intelligence reporting to clients.

 2. Execution & Architecture Implementation
 * Pipeline & Workflow Audits: Perform hands-on data audits to structure extraction, cleaning, storage, and transformation pipelines for client engagements.
 * Dashboarding & BI Delivery: Implement and maintain robust dashboards across traditional BI platforms and modern automated reporting tools.
 * Production Deployment: Move small-scale data scripts and machine learning models into production-level workflows to make client intelligence offerings scalable and automated.

 3. Mentorship & Operational Enablement
 * Team Supervision: Directly oversee and mentor junior and mid-level analysts and engineers on daily workflows, coding standards, and industry best practices.
 * Technical Documentation: Author detailed architecture documentation, user guides, and client offboarding materials to support seamless dashboard and database querying enablement.
 * Cross-Functional Collaboration: Serve as the core point of contact between engineering teams, data analysts, and account leads on technical deliverables.