Remote opportunity at
Security BenefitSenior Analytics Engineer
Everly is working to reshape life insurance around transparency and partnership. Many people buy a policy at a milestone moment and then set it aside, and…
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About This Role
Everly is working to reshape life insurance around transparency and partnership. Many people buy a policy at a milestone moment and then set it aside, and the company wants to change that relationship. This remote, US-based senior position is for an analytics engineer who will act as product owner of the analytics platform and as a hands-on leader of data platform engineering and governance. It is an individual contributor role…
Job Description
Everly is working to reshape life insurance around transparency and partnership. Many people buy a policy at a milestone moment and then set it aside, and the company wants to change that relationship. This remote, US-based senior position is for an analytics engineer who will act as product owner of the analytics platform and as a hands-on leader of data platform engineering and governance. It is an individual contributor role with wide influence over the company's data foundation.
The engineer is responsible for everything from raw data intake through transformations, the semantic layer, and the executive and operational dashboards that leaders, operations staff, and actuaries rely on. The stack covers Lambda, S3, AWS Glue, Step Functions, Snowflake, dbt, and Sigma, along with infrastructure-as-code and outside DataOps partners. Duties include maintaining an enterprise data model and dictionary, enforcing Snowflake security, designing versioned stores for policy, claims, billing, distribution, and customer data, and building database foundations for AI tooling. The engineer also sets service levels, data quality standards, and runbooks, and mentors a junior analytics engineer and a data scientist.
Governance is a central part of the role. The engineer helps satisfy GLBA and NAIC MDL-668 record-keeping expectations, gathers evidence for SOC 2 Type II reviews, supports HIPAA, CCPA/CPRA, and state breach notice rules, and explains the compromises behind platform choices to senior leadership. Occasional travel may be requested.
Responsibilities
- Set the analytics platform's roadmap, architecture, and tooling jointly with the Head of Data and IT
- Set and enforce SLAs, data quality benchmarks, and runbooks for the platform
- Oversee pipelines from ingestion through transformation to BI tools and data products
- Keep the company-wide data model, its dictionary, and the business rules current
- Put Snowflake masking, role-based access, and least-privilege controls into practice
- Design versioned stores for core insurance areas such as policy, claims, billing, distribution, and customer
- Shape the database foundation for AI tooling and models, covering vector stores and feature stores
- Build and maintain the semantic layer and executive and operational dashboards
- Keep actuarial data pipelines running, including Glue jobs
Requirements
- A degree in CS, data engineering, statistics, math, or an adjacent field, or equivalent hands-on work
- Eight or more years in analytics or data engineering work, or a near equivalent, with steadily larger scope
- Hands-on dbt work for transformation, modeling, and testing at scale
- Strong Snowflake experience, covering dynamic masking, RBAC, performance tuning, and cost control
- Practical experience with Lambda, S3, AWS Glue, and Step Functions
- Strong SQL, plus Python for pipeline work and automation
- A record of owning a BI roadmap and building executive and operational dashboards
- Background designing company-wide data models and semantic layers spanning many products and sources
- Understanding of data governance, quality frameworks, and privacy practice
- Experience with infrastructure-as-code such as Terraform or CloudFormation
- Working knowledge of GLBA and NAIC MDL-668 for US life and annuity carriers
- Having owned a product or platform roadmap in a technical setting
Qualifications
- Life insurance or annuity background, strongly preferred; wider financial services considered
- Exposure to actuarial data workflows
- Familiarity with observability tools such as Monte Carlo, Great Expectations, or dbt tests
- Comfort with Git workflows and CI/CD pipelines for data work
- Spark experience through Glue or EMR
- Working understanding of SOC 2 Type II audit frameworks and how evidence is gathered
- HIPAA exposure in underwriting or health-related data
- Awareness of CCPA/CPRA and multi-state breach notification duties
- Experience bringing vendor or consultant work in-house
- Some hands-on time with machine learning pipelines or feature engineering for modeling teams
Core Skills
Benefits
- Annual incentive bonus
- Flexible time off, company holidays, a day for significant personal milestones, and a volunteer day
- Paid parental leave after 3 months of service
- Medical, dental, and vision coverage
- 401(k) with company match, plus a profit sharing and savings plan
- Short- and long-term disability coverage, flexible spending account, and life insurance
- Educational assistance
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is this role remote?
The role is remote within the US, and occasional travel may come up.
What is the salary range?
The posting gives $130,000 to $152,000 for most US locations. Other locations follow the range for that location, as stated in the offer letter.
What experience is required?
The posting asks for 8+ years in analytics or data engineering, with hands-on dbt, Snowflake, and AWS data service experience.
How do I apply?
Applicants submit a resume through the company's career section, per the posting.
Sample Interview Questions
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