Director, Data Engineering – Analytics

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead the strategy, architecture, delivery, and ongoing enhancement of Relation’s enterprise data engineering and analytics capabilities.

• Oversee the complete data platform and analytics function, encompassing execution and results.

• Convert executive and business objectives into a tangible data and analytics roadmap and drive execution.

• Act as the primary authority for executives, business leaders, auditors, and carrier partners regarding data, reporting, and analytics issues.

• Provide executive-level reporting on platform health, delivery progress, data quality, and data risk.

• Collaborate with IT, Information Security, Finance, Operations, and business leadership to secure source access, implement controls, and promote adoption.

• Design, construct, and maintain data pipelines for production sourced from core brokerage and enterprise systems.

• Manage data processes from business requirements through profiling, modeling, transformation, validation, delivery, and production support.

• Diagnose failed loads, data inconsistencies, and performance issues to determine root causes.

• Create curated reusable datasets and data models for essential business domains.

• Define KPI logic and Power BI semantic models.

• Develop executive dashboards and self-service reporting while facilitating stakeholder adoption.

• Make architectural decisions regarding the lakehouse platform, medallion layers, ELT patterns, and orchestration.

• Guide AI coding agents by breaking down initiatives, delegating tasks, reviewing outputs, and delivering results.

• Integrate AI-driven validation, reconciliation, anomaly detection, and agent-based code/output review into data processes.

• Establish and uphold standards for secure and efficient AI usage, collaborating with Information Security on AI governance.

• Identify and implement AI and automation opportunities for reporting, reconciliation, and data entry.

• Construct and manage LLM-powered data workflows for document and data extraction, classification, and validation.

• Maintain the platform in a structured, documented, tested, and reproducible manner.

• Assess and adopt AI capabilities that enhance speed, quality, or coverage.

• Lead, mentor, and nurture data engineering and analytics professionals.

• Review code and data models, collaborate on challenging issues, and elevate technical standards.

• Manage data request intake, prioritization, timelines, and communication with stakeholders.

• Establish GitHub workflows, pull request reviews, GitHub Actions CI/CD, testing, documentation, and production support standards.

• Set objectives, provide feedback and performance management, and assist in succession and development planning.

• Define and implement data quality controls, testing, monitoring, incident response, governance, lineage, and certified datasets.

• Ensure access controls and privacy-by-design are in place for sensitive client and financial information.

• Perform additional assigned projects, duties, and tasks.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Information Systems, or a related field, or equivalent practical experience.

• At least 10 years of progressively responsible hands-on experience in data engineering, analytics engineering, data architecture, data analytics, or related technology roles.

• Proven experience managing a data platform or analytics function and achieving outcomes aligned with business priorities.

• Prior leadership experience in guiding and developing technical teams, project management, or complex cross-functional initiatives.

• Current hands-on experience with production SQL, Python, and PySpark.

• A strong history of owning data processes from start to finish and delivering quantifiable business results.

• Extensive hands-on experience with AI throughout the engineering lifecycle, including agentic coding tools, LLM APIs, and automated validation.

• Proficiency in data modeling, MDM concepts, and entity resolution across systems and acquired agencies.

• Expertise in SQL, Python, and Spark (PySpark).

• Knowledgeable in lakehouse and medallion architecture, ELT, orchestration, and reliable pipeline patterns.

• Skilled in data quality testing, reconciliation, observability, and production support.

• Familiar with role-based access controls, secure data handling, and audit-ready processes.

• Experience in specifying, orchestrating, and reviewing AI coding agents, as well as evaluating AI-generated code, data, and analysis.

• Excellent written and verbal communication skills, including the ability to present to and advise executives.

• Capable of clearly explaining data, trade-offs, and risks to non-technical stakeholders.

• Highly organized, able to juggle multiple concurrent initiatives and competing executive priorities.

• Detail-oriented with a strategic, enterprise-level perspective.

🏝️ Benefits

• Competitive pay.

• Family health and wellness programs.

• 401K.

• Employee assistance programs.

• Paid time off.

• Paid holidays.

• Opportunities for career advancement and development.

• Discretionary annual incentive program, subject to program rules and individual and organizational performance.