Pay
$154K–$226K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,013 postings in the last year. Stated ranges, not salaries paid.
Reads like a Data Leadership role: running a data team.
Plano, TX, USA
Open 3 months, first seen by us 109 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Define data and AI platform strategy and roadmap for Specialty Distribution
Oversee design and support of data pipelines on Databricks and Azure services
Deploy AI solutions and agents into production and scale them across the business
Establish engineering standards, CI/CD, and SDLC discipline
Build and develop a high-performing AI and data engineering organization
Own and evolve the Specialty Distribution Data strategy
Oversee the design, build, optimization, and support of modern data pipelines
Deploy incubated AI solutions into production and scale successful capabilities across the business
Establish high-quality engineering practices for modular code
Build, lead, and develop a high-performing AI and data engineering organization
Bachelor’s degree in business, data science, computer science, information systems, engineering, or a related field.
Proven experience working with Director, VP, and C-suite stakeholders in a large-scale, matrixed enterprise environment.
Skills & Experience to Be Successful: Required: - Bachelor’s degree in business, data science, computer science, information systems, engineering, or a related field. - 10+ years of progressive experience in data engineering, AI, analytics platforms, software engineering, technology leadership, or related roles.
- Excellent leadership, communication, stakeholder management, and executive presentation skills. - Master’s degree in business, data science, computer science, information systems, engineering, or a related field. (preferred) - Experience in the insurance industry, including awareness of risk, regulatory, compliance, privacy, and data protection considerations. (preferred)
Bridge Specialty Group creates a seamless way to connect the varying needs of our retail partners with the market clout and talents of our wholesale entities.
In the employer’s words · Read in context
Open 3 monthsWe first saw this posting 109 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$154K–$226K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,013 postings in the last year. Stated ranges, not salaries paid.
Day 109
Up longer than most. Similar jobs usually come down between day 7 and day 55.
Well past Bbinsurance’s usual: its jobs come down by about day 28.
From 8,345 similar postings that came down, and 22 of Bbinsurance’s. Coming down is not always a hire.
9 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Experience mentoring or coaching teams on engineering excellence, data engineering standards, DevSecOps, platform reliability, and AI enablement. (preferred) - Software engineering background in Java, .NET, or similar enterprise application development technologies. (preferred) About Us:
- Strong technical understanding of modern data platforms and cloud ecosystems, including Azure, Databricks, Data Lake, Azure Data Factory, Synapse, SQL, Power BI, Denodo, Snowflake, Cosmos DB, Boomi, Azure AI Foundry, and related technologies. - Working knowledge of Python, SQL, Spark, data orchestration, data integration, data modeling, data governance, and data platform operations. - Experience implementing modern SDLC practices, including CI/CD, automated testing, branching strategies, Infrastructure as Code, environment management, and DevSecOps practices.
- Ensure the reliable operation of data services, platforms, pipelines, integration services, orchestration tools, reporting data sets, and supporting infrastructure. - Oversee the design, build, optimization, and support of modern data pipelines using technologies such as Databricks, Delta Lake, Azure Data Services, Azure Data Factory, Azure Data Lake, Synapse, SQL, and related platforms. - Establish high-quality engineering practices for modular code, reusable components, automated deployments, environment management, branching strategies, CI/CD pipelines, and SDLC discipline.
- Deep experience delivering data and AI solutions at scale with measurable business value. - Strong technical understanding of modern data platforms and cloud ecosystems, including Azure, Databricks, Data Lake, Azure Data Factory, Synapse, SQL, Power BI, Denodo, Snowflake, Cosmos DB, Boomi, Azure AI Foundry, and related technologies. - Working knowledge of Python, SQL, Spark, data orchestration, data integration, data modeling, data governance, and data platform operations.
- Experience securing data across multi-national environments with geo-specific regulatory requirements such as GDPR, LGPD, or similar frameworks. (preferred) - Hands-on familiarity with Terraform, Bicep, Azure DevOps, Key Vault, Infrastructure as Code, and automated deployment practices. (preferred) - Experience mentoring or coaching teams on engineering excellence, data engineering standards, DevSecOps, platform reliability, and AI enablement. (preferred)
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New Data Leadership postings at the employers we follow are up 7% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
Built on meritocracy, our unique company culture rewards self-starters and those who are committed to doing what is best for our customers.
Bridge Specialty Group is seeking a Head of AI & Data Platform Engineering – Specialty Distribution to join our growing team in Plano, TX or Daytona Beach, FL!
The Head of AI and Data Platforms is responsible for leading the Specialty Distribution Data and AI Engineering function and defining the strategy, operating model, and execution roadmap for enterprise-grade data and AI products. This role enables the business to consume trusted data, analytics, reporting, insights, automation, and AI solutions that improve decision-making, operational performance, customer experience, and growth.
This leader will oversee the design, delivery, governance, and ongoing operation of scalable data platforms, data products, AI solutions, and engineering practices. The role requires a strategic technology leader who can partner with enterprise technology, business leadership, security, analytics, and engineering teams while also driving modern software engineering, DevOps, cloud, and data platform practices across the organization.
How You Will Contribute:
Strategy, Architecture, and Governance
Own and evolve the Specialty Distribution Data strategy while contributing to broader Enterprise Data, AI, and Specialty Distribution AI strategies.
Develop and maintain roadmaps that translate business priorities into executable data, analytics, and AI platform initiatives.
Establish scalable architecture patterns, engineering standards, governance practices, and delivery frameworks for data and AI solutions.
Implement extensible and reusable data products that align with enterprise models, technology standards, security controls, and platform patterns.
Manage data and AI risk, including compliance with enterprise data, AI, security, privacy, and regulatory policies.
Partner with enterprise architecture, security, infrastructure, software engineering, analytics, and business leadership teams to ensure solutions are secure, scalable, reliable, and aligned to enterprise strategy.
Data Platform Operations and Engineering
Build and lead a best-practice data and AI engineering operating model, including team structure, processes, tools, standards, governance, and ways of working.
Ensure the reliable operation of data services, platforms, pipelines, integration services, orchestration tools, reporting data sets, and supporting infrastructure.
Oversee the design, build, optimization, and support of modern data pipelines using technologies such as Databricks, Delta Lake, Azure Data Services, Azure Data Factory, Azure Data Lake, Synapse, SQL, and related platforms.
Establish high-quality engineering practices for modular code, reusable components, automated deployments, environment management, branching strategies, CI/CD pipelines, and SDLC discipline.
Drive continuous improvement across data engineering, DevOps, data operations, platform reliability, and delivery processes.
Support data and BI developers by operationalizing analytics, reporting workflows, curated datasets, semantic layers, and visualization-ready data products.
AI Engineering and Product Delivery
Lead the delivery of AI solutions, AI agents, automation capabilities, and intelligent products in partnership with Enterprise AI, business teams, and platform stakeholders.
Deploy incubated AI solutions into production and scale successful capabilities across the business to expand adoption, value realization, and operational coverage.
Ensure AI products are designed with appropriate governance, security, compliance, monitoring, responsible AI practices, and measurable business outcomes.
Partner with Enterprise AI and Communications teams to support training, enablement, and adoption of AI tools such as Microsoft Copilot and other approved enterprise AI platforms.
Data Project Delivery and Business Enablement
Deliver data and AI initiatives from concept through production, ensuring solutions are aligned to business priorities, enterprise standards, and measurable value.
Build strong relationships with executive stakeholders, business leaders, product owners, analytics teams, and technology partners to translate business needs into effective data and AI capabilities.
Manage and prioritize a backlog of enhancements, small changes, platform improvements, and new data product needs.
Support onboarding and integration of acquisitions into the company’s data, analytics, AI, and systems landscape.
Identify inefficiencies across technical pipelines, platform operations, and engineering processes, and design pragmatic solutions that improve speed, quality, reliability, and scalability.
Leadership and Talent Development
Build, lead, and develop a high-performing AI and data engineering organization capable of delivering at enterprise scale.
Provide clear direction, coaching, performance management, and professional development for leaders, engineers, architects, and platform specialists.
Foster a culture of accountability, collaboration, innovation, engineering excellence, security awareness, and continuous improvement.
Champion modern data engineering, DevSecOps, cloud, and responsible AI practices across the organization.
Communicate effectively with senior executives, technical teams, business stakeholders, and cross-functional partners, translating complex technology concepts into clear business value.
Licenses and Certifications:
Skills & Experience to Be Successful:
Required:
Bachelor’s degree in business, data science, computer science, information systems, engineering, or a related field.
10+ years of progressive experience in data engineering, AI, analytics platforms, software engineering, technology leadership, or related roles.
Proven experience working with Director, VP, and C-suite stakeholders in a large-scale, matrixed enterprise environment.
Demonstrated success leading data, AI, engineering, or platform teams at scale, including people leadership, operating model design, and delivery accountability.
Experience managing large technology budgets, vendor relationships, delivery portfolios, and enterprise technology roadmaps.
Deep experience delivering data and AI solutions at scale with measurable business value.
Strong technical understanding of modern data platforms and cloud ecosystems, including Azure, Databricks, Data Lake, Azure Data Factory, Synapse, SQL, Power BI, Denodo, Snowflake, Cosmos DB, Boomi, Azure AI Foundry, and related technologies.
Working knowledge of Python, SQL, Spark, data orchestration, data integration, data modeling, data governance, and data platform operations.
Experience implementing modern SDLC practices, including CI/CD, automated testing, branching strategies, Infrastructure as Code, environment management, and DevSecOps practices.
Strong problem-solving skills with the ability to navigate ambiguity, identify root causes across technical and organizational layers, and drive practical solutions.
Excellent leadership, communication, stakeholder management, and executive presentation skills.
Master’s degree in business, data science, computer science, information systems, engineering, or a related field. (preferred)
Experience in the insurance industry, including awareness of risk, regulatory, compliance, privacy, and data protection considerations. (preferred)
Experience securing data across multi-national environments with geo-specific regulatory requirements such as GDPR, LGPD, or similar frameworks. (preferred)
Hands-on familiarity with Terraform, Bicep, Azure DevOps, Key Vault, Infrastructure as Code, and automated deployment practices. (preferred)
Experience mentoring or coaching teams on engineering excellence, data engineering standards, DevSecOps, platform reliability, and AI enablement. (preferred)
Software engineering background in Java, .NET, or similar enterprise application development technologies. (preferred)
About Us:
Bridge Specialty Group creates a seamless way to connect the varying needs of our retail partners with the market clout and talents of our wholesale entities. Our more than 25 niche-focused brands reflect our deep experience and specialization in construction, general casualty, environmental liability, professional liability, health care, public entity, workers’ comp, property and personal lines.
With more than 50 locations and more than 2,000 team members throughout the United States and Europe, Bridge has access to more than 200 standard and excess & surplus lines carriers that support our $7+ billion premium book.
Our focus is on bringing the power of collective size and specialty to the wholesale brokerage marketplace. Bridge Specialty Group – aligning risk with greater reach.
Teammate Benefits & Total Well-Being
We go beyond standard benefits, focusing on the total well-being of our teammates, including:
Not reflective of all benefits. Enrollment waiting periods or eligibility criteria may apply to certain benefits. Benefit details and offerings may vary for subsidiary entities or in specific geographic locations.
Recruiting Vendor Disclosure Statement
Brown & Brown does not accept unsolicited resumes from external recruiters, recruitment vendors or employment agencies ("Recruiting Vendors"). Recruiting Vendors must have a valid written agreement and received prior written authorization from an authorized Brown & Brown representative before submitting candidates for any publicly posted role. Any unsolicited resumes submitted to Brown & Brown or its employees become the property of Brown & Brown, and no fees will be paid for such submissions. Additional information regarding this policy can be found on our careers page.
The Power To Be Yourself
As an Equal Opportunity Employer, we are committed to fostering an inclusive environment comprised of people from all backgrounds, with a variety of experiences and perspectives, guided by our Diversity, Inclusion & Belonging (DIB) motto, “The Power to Be Yourself”.
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Plano, TX, USA
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