Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps)
Summary The Lead Data & Analytics Architect is responsible for defining, designing, and governing the enterprise data ecosystem across cloud, onpremises, and hybrid environments. The role establishes ...
Summary The Lead Data & Analytics Architect is responsible for defining, designing, and governing the enterprise data ecosystem across cloud, onpremises, and hybrid environments. The role establishes ...
Google BigQuery Analytics Architect Location: Atlanta, GA ( Hybrid 2-3 days) Duration: 12 months We ... Data Strategy Development : * Define and implement the organization's data analytics strategy ...
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The Data & Analytics Architect actively participates in providing the overall direction of architecture across the entire Data and Analytics platform focused on the following four key verticals:
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$65.25 - $84/hr
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Intern Data Analytics Architect information
See salary details
$11.78 - $14.18
1% of jobs
$14.18 - $16.59
11% of jobs
$17.72 is the 25th percentile. Wages below this are outliers.
$16.59 - $18.99
28% of jobs
The median wage is $20.89 / hr.
$18.99 - $21.39
13% of jobs
$21.39 - $23.80
11% of jobs
$26.05 is the 75th percentile. Wages above this are outliers.
$23.80 - $26.20
13% of jobs
$26.20 - $28.61
12% of jobs
$28.61 - $31.01
5% of jobs
$31.01 - $33.41
2% of jobs
$33.41 - $35.82
3% of jobs
$35.82 - $38.22
2% of jobs
$11
$22
$38
How much do intern data analytics architect jobs pay per hour?
What does an Intern Data Analytics Architect do?
What is the difference between Intern Data Analytics Architect vs Data Analyst Intern?
| Aspect | Intern Data Analytics Architect | Data Analyst Intern |
|---|---|---|
| Required Credentials | Basic knowledge of data architecture, SQL, and analytics tools | Basic understanding of data analysis, Excel, and visualization tools |
| Work Environment | Assists in designing data systems, working with data engineers | Supports data analysis projects, creating reports and dashboards |
| Employer & Industry Usage | Used in tech, finance, and consulting firms focusing on data infrastructure | Common in marketing, finance, and business sectors for data insights |
The Intern Data Analytics Architect role focuses on supporting the design and implementation of data systems, requiring knowledge of data architecture and analytics tools. In contrast, a Data Analyst Intern primarily analyzes data sets to generate reports and insights. Both roles are entry-level internships but differ in their focus—one on data infrastructure, the other on data interpretation.
What are the key skills and qualifications needed to thrive as an Intern Data Analytics Architect, and why are they important?
What kinds of projects and responsibilities can an Intern Data Analytics Architect expect to work on?
Hylant rating
9.8
Based on 5 frontline employees who took The Breakroom Quiz
2nd of 263 rated insurance
Job description
The Opportunity:
The Lead Data Architect exists to define, own, and evolve Hylant's enterprise application and information architecture. This role ensures that current data initiatives are intentionally designed to meet today's analytical needs while enabling future innovation through scalable, secure, and wellgoverned platforms. The position serves as a technical authority and strategic partner across data engineering, analytics, and business teams. This role will be measured by its contribution to business outcomes such as operational efficiency, adoption of self-service data products, and AI agent effectiveness.
In This Role You Will Execute On:
Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps).
Responsible for application architecture (platform, tools, technologies) and information architecture (data models, data flow, data structures and data access)
Translate business and analytical requirements into scalable, secure, and feasible data architecture designs that support both nearterm delivery and longterm innovation.
Guide requirements gathering, backlog shaping, and solution design to ensure initiatives align with established architectural standards and futurestate roadmaps.
Lead the design of analytical data models, including dimensional and star schema designs for curated, businessready data layers.
Design and oversee endtoend data pipelines, including sourcetotarget mappings, transformation logic, and serving strategies.
Establish architectural patterns and standards for data ingestion, transformation, storage, governance, and analytics consumption.
Establish and enforce data governance frameworks, standards, and policies to ensure data quality, security, and compliance.
Ensure the integrity, quality, and validation of data across the full lifecycle, from source systems through curated datasets and reporting layers.
Partner closely with data engineering and analytics teams to provide architectural guidance throughout delivery while remaining accountable for solution quality. Mentor and guide the lead data engineer.
Own the Data Strategy & Lifecycle Management, treating EDW domains as data products with SLAs, ownership, and lifecycle
Contribute to AI, Machine Learning, and Analytics Enablement Roadmap.
Responsible for overseeing, integrating, and optimizing AI agents in data pipelines and ensuring the right mix of human and AI involvement. Ensure responsible use of AI agents and automation in data integration, transformation, and delivery.
Understand and own relationships with external support providers and vendors as needed.
Evaluate and recommend platform capabilities and emerging technologies to continuously improve performance, scalability, and usability of the data ecosystem. Ensure solutions and system are scalable, re-usable, and cost optimized.
Perform other duties and special projects as requested.
In This Role You'll Need:
Prefer bachelor's degree in computer science, data science, engineering, or a related field, or equivalent practical experience.
Insurance industry experience, including familiarity with data domains such as policy, claims, billing, underwriting, or risk.
Six or more years of experience in data architecture, analytics architecture, or enterprise data platform design.
Demonstrated experience designing and delivering data platforms built on Azure based technologies as well as with multi-cloud or hybrid environments.
Hands on experience with DevOps (CI/CD process), event streaming and processing, AI/ML toolset, Azure Databricks, Microsoft Data Factory, Delta Lake, Unity Catalog, and Azure cloud services.
Strong experience designing analytical data models, including dimensional and star schema approaches.
Advanced SQL skills and working proficiency with PySpark for data transformation and modeling.
Experience designing and validating end-to-end data pipelines, including data quality and reconciliation processes.
Ability to clearly communicate complex technical concepts to both technical and non-technical audiences.
Experience managing a team and in establishing an Architecture Review Board, Design Reviews, and Data Standards and Conventions.
Must be willing and able to travel for in-person meetings at least on a quarterly basis
Ability and willingness to travel by car or airplane for meetings, conferences, or other business-related functions.
Must be legally authorized to work in the United States
Why Hylant?
A multi-year recipient of Best Places to Work in Insurance, Hylant is a full-service insurance brokerage with over 20 offices in eight states. And since the founding of our family-owned business over 90 years ago, we made a promise to strengthen and protect the businesses, employees and communities of our client family by embracing them as our own. We're more than an insurance brokerage firm and you're more than a client, employee or neighbor. You're family. And that's just the way we treat you.
Hylant is proud to be an equal opportunity workplace. All qualified applicants will receive consideration for employment without regard to race, marital status, sex, age, color, religion, national origin, Veteran status, disability or any other characteristic protected by law. If you have a disability or special need that requires accommodation, please let us know. Hylant participates in E-Verify.
About Hylant
Sourced by ZipRecruiter
Industry
Insurance services
Company size
501 - 1,000 Employees
Headquarters location
Toledo, OH, US
Year founded
1935