Director, Data Engineering – Analytics

Job not on LinkedIn

🔥 6 minutes ago

🇺🇸 United States – Remote

💵 $178k - $294k / year

⏰ Full Time

🔴 Lead

🚰 Data Engineer

👻 Ghost score 2%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Relation Insurance Services

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

💼 Consulting

🏗️ Construction

🏥 Healthcare

Consulting • Construction • Healthcare

Relation Insurance Services is a trusted partner in insurance brokerage, offering personalized solutions across various sectors. The company emphasizes building strong relationships based on trust and understanding client challenges, whether in personal or business contexts. With expertise in industries such as agribusiness, construction, finance, and technology, Relation Insurance Services leverages data-driven insights and long-term carrier relationships to navigate the complexities of insurance, ensuring clients feel safer and more in control of their insurance decisions.

📋 Description

• Lead the strategy, architecture, delivery, and continuous improvement of Relation’s enterprise data engineering and analytics capabilities • Own the data platform and analytics function end to end, including execution and outcomes • Translate executive and business priorities into a practical data and analytics roadmap and drive execution • Serve as the accountable authority for executives, business leaders, auditors, and carrier partners on data, reporting, and analytics matters • Provide executive-ready reporting on platform health, delivery progress, data quality, and data risk • Partner with IT, Information Security, Finance, Operations, and business leadership to obtain source access, implement controls, and drive adoption • Design, build, and maintain production data pipelines from core brokerage and enterprise systems • Own data processes from business need through profiling, modeling, transformation, validation, delivery, and production support • Troubleshoot failed loads, data discrepancies, and performance issues to root cause • Build curated reusable datasets and data models for core business domains • Define KPI logic and Power BI semantic models • Build executive dashboards and self-service reporting and drive stakeholder adoption • Make architecture decisions for the lakehouse platform, medallion layers, ELT patterns, and orchestration • Direct AI coding agents by decomposing initiatives, delegating work, reviewing outputs, and shipping results • Build AI-driven validation, reconciliation, anomaly detection, and agent-based code/output review into data processes • Establish and enforce standards for secure and effective AI use and partner with Information Security on AI governance • Identify and deliver AI and automation opportunities for reporting, reconciliation, and data entry • Build and operate production LLM-powered data workflows for document and data extraction, classification, and validation • Keep the platform structured, documented, tested, and reproducible • Evaluate and adopt AI capabilities that improve speed, quality, or coverage • Lead, coach, and develop data engineering and analytics professionals • Review code and data models, pair on difficult problems, and raise technical standards • Manage data request intake, prioritization, timelines, and stakeholder communication • Establish GitHub workflows, pull request review, GitHub Actions CI/CD, testing, documentation, and production support standards • Set goals, provide feedback and performance management, and support succession and development planning • Define and enforce data quality controls, testing, monitoring, incident response, governance, lineage, and certified datasets • Ensure access controls and privacy-by-design for sensitive client and financial data • Perform other assigned projects, duties, and tasks

🎯 Requirements

• Bachelor’s degree in Computer Science, Information Systems, or a related field, or equivalent practical experience • Minimum 10 years of progressively responsible hands-on experience in data engineering, analytics engineering, data architecture, data analytics or related technology roles • Experience owning a data platform or analytics function and delivering outcomes against business priorities • Previous leadership experience leading and developing technical teams, people leaders, projects, or complex cross-functional initiatives • Current hands-on production SQL, Python, and PySpark experience • Track record of owning data processes end to end and delivering measurable business outcomes • Deep, daily, hands-on use of AI across the engineering lifecycle, including agentic coding tools, LLM APIs, and automated validation • Expertise in data modeling, MDM concepts, and entity resolution across systems and acquired agencies • Expertise in SQL, Python, and Spark (PySpark) • Expertise in lakehouse and medallion architecture, ELT, orchestration, and pipeline reliability patterns • Expertise in data quality testing, reconciliation, observability, and production support • Expertise in role-based access controls, secure data handling, and audit-ready processes • Experience specifying, orchestrating, and reviewing AI coding agents and evaluating AI-generated code, data, and analysis • Exceptional written and verbal communication skills, including presenting to and advising executives • Ability to explain data, tradeoffs, and risk clearly to non-technical partners • Highly organized, able to manage 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 • Career advancement and development opportunities • Discretionary annual incentive program, subject to program rules and individual and organizational performance