Senior Analytics Engineer

About this role

About Us:
At Everly, our vision is to change the paradigm of insurance. We know life insurance can be confusing and complex. We know that most people purchase life insurance at a milestone moment and file it away for the future. We want to change how people think about, buy, and use life insurance by being a partner in life’s journey. We are focused on making things that matter, making meaningful connections, and making things work WAY better. Our goal is to provide radically transparent, consumer-first insurance solutions.
We are looking for people with a continuous improvement mindset. Those who think the opposite of “This is how we’ve always done it”. We want people on our team who are always asking “How can we do this better?”
Our company values are a guide to our behavior and help inform our decisions. We want people who embody those values of breaking down barriers, owning the outcome, embracing the journey, and sparking joy.
This is a remote position based in the US with occasional travel.
About the role:
We're looking for a Senior Analytics Engineer, Data Platform to serve as the product owner of our analytics platform and hands-on technical lead for data platform engineering and governance. This is a senior individual contributor role with outsized impact - you'll operate as the technical authority for our data platform, setting direction, owning the roadmap, and rolling up your sleeves to build. In this role, you'll own the full data lifecycle from ingestion and transformation through to the semantic layer and executive dashboards that our leadership, operators, and actuaries depend on daily. Beyond building, you'll govern, ensuring our platform is compliant, well-documented, and resilient as the business scales. You'll work closely with the Head of Data, Head of Modeling, cross-stream data stewards, actuarial team, and third-party infrastructure partners. You'll also serve as a technical mentor to a junior Analytics Engineer and Data Scientist. The ideal candidate has deep hands-on engineering skills, a product mindset, and the communication ability to translate complex platform trade-offs to senior leadership. If you thrive at the intersection of data engineering, governance, and business intelligence — and want to shape the data foundation of a company reimagining life insurance — this role is for you.
What You’ll Do:
Platform Product Ownership

• Own the analytics platform roadmap — prioritizing improvements, architecture decisions, and tooling enhancements in partnership with IT and the Head of Data, Analytics and AI Solutions

• Define and enforce platform SLAs, data quality standards, and operational runbooks

• Serve as technical mentor to the Analytics Engineer/Data Scientist

Data Pipeline Ownership

• Own the end-to-end data pipeline from ingestion through transformation and delivery into BI tools and data products across our AWS stack (Step Functions, Glue, Snowflake, dbt, Sigma)

• Partner with third-party vendors to maintain DataOps infrastructure using infrastructure-as-code practices

• Monitor pipeline health and drive timely resolution of data issues with providers and consumers

Enterprise Data Modeling & Governance

• Maintain and evolve an enterprise data model, data dictionary, and business rules agnostic across sources, insurance products, and distributors

• Enforce Snowflake security best practices — masking policies, RBAC, and least-privilege access — aligned to GLBA NPI/NPI-H classification requirements

• Champion data governance, lineage, and quality standards; support NAIC MDL-668 audit trails, SOC 2 Type II evidence collection, and adherence to CCPA/CPRA, HIPAA, and state breach notification requirements

Systems of Record & AI Data Infrastructure

• Design and maintain systems of record for core insurance domains (policy, claims, billing, distribution, customer) with proper versioning, effective dating, and audit history

• Own database design and management for AI tools and models, including vector databases, feature stores, and model input/output pipelines

Semantic Layer & BI

• Design and maintain a semantic layer enabling natural language insight discovery

• Own executive and operational dashboards from board-level reporting down to day-to-day operations

• Set BI development standards for the Analytics Engineer/Data Scientist to execute against

Actuarial & Advanced Analytics Support

• Maintain and enhance actuarial data pipelines including distributed compute and Glue Jobs for data curation

• Advise on data architecture decisions supporting future AI/ML and modeling use cases

Skills and Experience:

• Bachelor’s degree in computer science, Data Engineering, Statistics, Mathematics, or a related field — or equivalent work experience

• 8+ years of experience in analytics engineering, data engineering, or a closely related role, with demonstrated progression in scope and ownership

• Hands-on experience with dbt (data build tool) for transformation, data modeling, and testing at scale

• Strong proficiency with Snowflake, including dynamic data masking, RBAC, performance optimization, and cost governance

• Hands-on experience with AWS data services including Glue, Step Functions, S3, and Lambda

• Strong SQL proficiency; Python required at this level (data pipeline development, scripting, automation)

• Demonstrated experience owning a BI delivery roadmap and building dashboards for executive and operational audiences

• Demonstrated experience building and maintaining enterprise data models and semantic layers in a multi-product, multi-source environment

• Strong understanding of data governance, data quality frameworks, and privacy best practices

• Hands-on experience with infrastructure-as-code tools (Terraform, CloudFormation, or similar)

• Working knowledge of data privacy and security compliance frameworks relevant to US life and annuity carriers, including GLBA, NAIC MDL-668.

• Experience owning or contributing to a…