Divisional Data Software Engineer III
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Job Description
Divisional Data Software Engineer building scalable data pipelines and cloud integrations for an insurance company. Designing data architecture, improving reliability, and mentoring engineers.
Responsibilities:
- Leads technical discovery and translates complex divisional requirements into data architecture, interfaces, and delivery plans
- Designs, builds, and operates scalable, secure, and resilient data ingestion, ELT, and integration services
- Develops reusable frameworks, libraries, and patterns that improve engineering consistency and delivery speed
- Designs dimensional and other fit-for-purpose data models; optimizes storage, query performance, and compute utilization
- Establishes automated testing, data quality controls, monitoring, alerting, and recovery practices
- Leads investigation of complex data defects and production incidents; drives root cause analysis and durable remediation
- Ensures solutions meet requirements for privacy, security, governance, lineage, and retention
- Facilitates technical reviews and makes recommendations on tools, design tradeoffs, and implementation approaches
- Partners with product, analytics, architecture, and business stakeholders to prioritize work and manage dependencies
- Mentors engineers through pairing, design feedback, code review, and sharing engineering practices
- Communicates delivery status, technical risks, operational health, and data limitations to stakeholders
Requirements:
- Bachelor's Degree in Computer Science, Data Science, Software Engineering, Information Systems, or a related field; or an equivalent combination of education and experience
- Five (5) or more years in data engineering, software engineering, data integration, or related work
- One (1) or more years of Insurance industry experience
- Knowledge of data architecture, data modeling, distributed processing, and pipeline orchestration
- Knowledge of cloud data platforms, APIs, and scalable integration patterns
- Skills in SQL and Python or another production programming language
- Skills in testing, observability, performance tuning, and production incident response
- Skills in technical communication, stakeholder partnership, and mentoring
- Ability to balance reliability, security, maintainability, delivery time, and cost
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