Director, Data Engineering – Business Applications

PEAK6

Director, Data Engineering responsible for enterprise data engineering and business applications at PEAK6. Collaborating with leaders to align data infrastructure with strategic objectives.

Posted 7/1/2026full-timeRemote • Ohio, Texas • 🇺🇸 United StatesLeadWebsite

Tech Stack

Tools & technologies

AWSAzureCloudETL

About the role

Key responsibilities & impact

Define and execute the strategic roadmap for FOCUS’s enterprise data engineering platform, including data pipelines, ETL/ELT processes, data lakes, data warehouses, and integration frameworks
Establish architectural standards for data ingestion, transformation, storage, and access that support analytics, reporting, and AI/ML use cases
Partner with business and technology leaders to prioritize data platform investments and ensure alignment with enterprise strategy and regulatory requirements
Provide executive-level reporting on platform health, data quality, and delivery outcomes
Own the lifecycle management of FOCUS’s business application portfolio, including policy administration, agency management, billing, claims, and document management systems
Oversee vendor relationships, licensing, contract renewals, and SLA performance for all business applications
Lead application rationalization, modernization, and integration efforts to improve operational efficiency and reduce technical debt
Partner with business stakeholders to evaluate new application capabilities and drive adoption of technology solutions that improve productivity and support FOCUS’s growth strategy
Lead, grow, and develop a high-performing team of data engineers, integration developers, and business application specialists
Drive talent strategy, succession planning, performance management, and professional development across the function
Establish engineering standards, development practices, and operational KPIs for the team
Directly manages Data Engineering team leads/managers and Business Applications managers, and may directly manage senior individual contributors (e.g., Principal Data Engineers, Senior Application Analysts)

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field required
Master’s degree in Computer Science, Data Science, Information Systems, or Business Administration (MBA) strongly preferred
Minimum of 10+ years of experience in data engineering, data architecture, or enterprise application management, with at least 4 years in a senior leadership role managing technical teams
Demonstrated experience designing and operating large-scale data platforms using modern cloud technologies (e.g., Azure, AWS, Snowflake, Databricks) within the insurance, financial services, or other highly regulated industries strongly preferred
Proven track record of managing enterprise business application portfolios (e.g., policy administration, agency management, billing, or claims systems) and leading application modernization or migration initiatives
Experience building and developing high-performing engineering teams, including hiring and growing senior individual contributors and team leads
Experience engaging with and presenting to executive and C-suite stakeholders on technology strategy, platform investments, and delivery outcomes.

Benefits

Comp & perks

healthcare benefits (medical, dental and vision, EAP)
competitive PTO
401k match
parental leave
HSA contribution match
paid subscription to the Calm app
generous external learning and tuition reimbursement benefits
ability to work remotely up to two days a week

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Data PipelinesETL/ELT ProcessesData LakesData WarehousesIntegration FrameworksData Quality ManagementApplication ModernizationTechnical Debt ReductionOperational KPIsExecutive Reporting

Soft Skills

Stakeholder EngagementTeam DevelopmentPerformance ManagementStrategic PlanningCommunication

Certifications

Bachelor’s Degree in Computer ScienceMaster’s Degree in Computer Science or Data Science (Preferred)