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Data Infrastructure Manager Jobs (NOW HIRING)

Data Infrastructure Architect

Manhattan, NY

$69.75 - $89.75/hr

The Data Infrastructure Architect will design, implement, and manage MOCJ's data architecture to support secure, scalable, and reliable data access, storage, integration, and analysis. This role will ...

Data Infrastructure Architect

Manhattan, NY

$69.75 - $89.75/hr

The Data Infrastructure Architect will design, implement, and manage MOCJ's data architecture to support secure, scalable, and reliable data access, storage, integration, and analysis. This role will ...

Software Engineer, Data Infrastructure

$117K - $140K/yr

... • Manage and evolve core platforms like Snowflake, our ML Datalake, orchestration infrastructure, and real-time ingestion systems. • Improve data reliability, consistency, and compliance ...

Showing results 41-60

Data Infrastructure Manager information

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$80.5K

$154K

$198K

How much do data infrastructure manager jobs pay per year?

As of Jul 24, 2026, the average yearly pay for data infrastructure manager in the United States is $154,028.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $197,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Infrastructure Manager, and why are they important?

To thrive as a Data Infrastructure Manager, you need expertise in data architecture, storage solutions, and database administration, typically backed by a degree in computer science or a related field. Familiarity with tools like SQL, Hadoop, cloud platforms (AWS, Azure, or Google Cloud), and certifications such as AWS Certified Solutions Architect are highly valuable. Strong leadership, problem-solving, and communication skills help you effectively manage teams and collaborate with stakeholders. These skills and qualities ensure reliable, scalable data systems that support organizational goals and data-driven decision making.

What is the difference between Data Infrastructure Manager vs Data Engineer?

AspectData Infrastructure ManagerData Engineer
Primary FocusOversees data systems, infrastructure, and architecture managementBuilds, develops, and maintains data pipelines and models
Required SkillsData architecture, leadership, project managementProgramming, ETL processes, database management
CertificationsCloud certifications, data management certificationsSQL, Python, cloud platform certifications
Work EnvironmentManagement, strategic planning, cross-team collaborationHands-on coding, data pipeline development

The Data Infrastructure Manager focuses on overseeing and managing the company's data systems and architecture, ensuring data availability and security. In contrast, Data Engineers are primarily responsible for designing and building the data pipelines and tools needed for data analysis. Both roles require technical skills and certifications, but the Manager role emphasizes leadership and strategic oversight, while the Engineer role is more technical and implementation-focused.

What are Data Infrastructure Managers?

Data Infrastructure Managers are professionals responsible for overseeing the design, implementation, and maintenance of an organization's data systems and architecture. They ensure that data storage, processing, and retrieval systems are efficient, secure, and scalable to meet business needs. Their role typically involves managing a team of data engineers, collaborating with IT and business units, and setting strategies for data governance and compliance. Data Infrastructure Managers play a critical role in enabling reliable data analytics and business intelligence by maintaining robust data pipelines and platforms.

What are some common challenges faced by Data Infrastructure Managers, and how can they be addressed?

Data Infrastructure Managers often encounter challenges such as scaling systems to handle increasing data volumes, ensuring high availability, and integrating new technologies with legacy systems. Addressing these issues typically involves proactive capacity planning, implementing robust monitoring and alerting tools, and fostering cross-functional collaboration with data engineering and IT security teams. Staying up-to-date with industry best practices and investing in staff training can also help mitigate these challenges and ensure reliable, scalable infrastructure.
More about Data Infrastructure Manager jobs
What cities are hiring for Data Infrastructure Manager jobs? Cities with the most Data Infrastructure Manager job openings:
What are the most commonly searched types of Data Infrastructure jobs? The most popular types of Data Infrastructure jobs are:
What states have the most Data Infrastructure Manager jobs? States with the most job openings for Data Infrastructure Manager jobs include:
Infographic showing various Data Infrastructure Manager job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $154,028 per year, or $74.1 per hour.
Vice President, Director of Data & Infrastructure

Vice President, Director of Data & Infrastructure

Methods+Mastery

Chicago, IL • On-site

$107K - $165K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 6 days ago


Job description

Position Overview

Methods+Mastery has an immediate opening for a talented, experienced Vice President, Director of Data & Infrastructure. In this senior leadership role within our Insights & Analytics team, you will act as the vital bridge between our data engineers, analysts, and Fortune 50 clients.


We are looking for an entrepreneurial, naturally curious leader who can architect modern data environments and seamlessly translate complex infrastructure, AI opportunities, and technical concepts into impactful business intelligence and clear, layman's terms for client stakeholders. The goal for this role is to create new intelligence offerings for our clients and to make current offerings more efficient, scaled, automated, and accurate.


Our team is growing at an amazing rate, and this is an opportunity to produce work for top clients in an entrepreneurial and collaborative environment that values team above all. We do great work – and hire only great people, too.


Methods+Mastery is actively committed to increasing our team’s diversity, aggressively eliminating systemic barriers to equity, and fostering a culture where different backgrounds and perspectives are respected and celebrated. We firmly believe a team of many diverse perspectives not only makes Methods+Mastery a better place to work, it is also critically important for producing creative and thoughtful work that represents the world we live in. To that end, we strongly encourage applications from women, people of color, members of the LGBTQ+ community, veterans, individuals with disabilities, and neurodivergent people.


The anticipated salary range for this position is $107,000-165,000.


Salary is based on a range of factors that include relevant experience, knowledge, skills, other job-related qualifications, and geography. A range of medical, dental, vision, 401(k) matching, paid time off, and/or other benefits also are available.


Key Responsibilities

1. Client Leadership & Strategic Communication

  • Bridge Technical & Business Realities: Act as the primary technical translator, communicating highly technical infrastructure capabilities, AI-driven offerings, or automated pipelines into clear business outcomes and financial impacts for non-technical clients.


  • Consultative Advisory: Consult clients with a strong POV on the marketing intelligence and data infrastructure industries, guiding them through trends, data maturity mapping, and best practices.


  • Strategic Delivery: Lead client briefs from start to finish, developing data methodologies, managing project scopes, timelines, and budgets, and delivering clear, concise business intelligence.



2. Solution Design & Infrastructure Architecture

  • Discovery and Assessment: Evaluate clients' needs and infrastructure landscapes by leading data audits to make recommendations for structuring data extraction, cleaning, storage, and delivery approaches.


  • Future-State Architecture: Work alongside analyst teams to design data infrastructures that use agency processes as a baseline and also flex to meet the bespoke needs of each client.


  • AI & Automation Readiness: Help scale data offerings and approaches beyond small-scale testing into production-level workflows, supporting regular intelligence reporting for clients. , Create an approach that is flexible enough to use both traditional BI tools and workflows required to feed modern machine learning models and autonomous agents.


3. Team Leadership & Technical Enablement

  • People Management & Mentorship: Lead, manage, and mentor junior and mid-level analysts and engineering teams, developing robust internal training modules and enforcing industry best practices.


  • Cross-Functional Collaboration: Serve as a decisive partner and liaison across all internal and external parties, including clients, data vendors, creative staff, strategists, and operations teams.


  • Client Offboarding & Change Management: Ensure long-term client success by overseeing technical enablement, building architecture documentation, and training client and internal teams to read new dashboards and query new databases.


Qualifications

Must-Haves:

  • Experience: 10+ years of total experience gained in digital marketing analytics, data engineering, or data infrastructure management.


  • Consulting & Scoping Skills: Proven ability to scope high-intensity projects, interpret client business needs, and craft tailored proposals inclusive of team roles, methodologies, and budgets.


  • Analytical & Technical Command: Expertise in analyzing and interpreting data from core client databases and standard marketing intelligence tools (e.g., Brandwatch, Netbase Quid, Talkwalker, Sprinklr), alongside advanced scripting capabilities for data automation.


  • Data Storytelling: Exceptional ability to spot data patterns quickly and distill complex technical data into concise stories, visualizations, scorecards, and executive-ready dashboards.


  • Communication: Elite verbal and written communication skills to effectively align and build trust with both deeply technical engineering teams and non-technical stakeholders.



Nice-to-Haves:

  • AI/MLOps Infrastructure: Experience with model deployment tools (Docker, Kubernetes), CI/CD for machine learning (DVC), AI workflow frameworks (LangChain, LlamaIndex), or Algorithmic Governance and Explainability (XAI).


  • Cloud & Infrastructure as Code (IaC): Hands-on experience setting up cloud sandboxes/proof of concepts and provisioning via IaC.


  • Dashboarding & Web Analytics: Experience with tools such as Tableau, Google Looker Studio, Power BI, Google Analytics, and the broader Google Cloud Platform suite.


  • Media & Consumer Intelligence: Experience with media monitoring tools (Onclusive, Zignal, Newswhip), real-time listening for crisis management, or consumer profiling tools (YouGov, MRI Simmons, GlobalWebIndex).


  • Process Automation: Knowledge of enterprise automation tools such as Microsoft Power Automate, Apps Script, and Google Cloud Workflows.