Senior Analytics Engineer

Carbon Data Solutions; United States; Remote; USD 130,000 - 152,000; Full time

Benefits offered by this job

Annual incentive bonus

Medical, Dental & Vision Insurance

401k with company match

Paid PTO and holidays

Educational Assistance

Job summary

Everly is seeking a Senior Analytics Engineer, Data Platform, to own the analytics platform as a product and serve as the technical lead for data engineering and governance. You’ll shape the data foundation, own the roadmap, and build across ingestion, transformation, semantic layer, and executive dashboards.

You’ll mentor teammates, collaborate with the Head of Data and actuarial teams, ensure compliance, and drive DataOps practices on AWS (Glue, Step Functions, Snowflake).

Qualifications

• Bachelor's degree in CS, data engineering, math, or equivalent experience.
• 8+ years in analytics/data engineering with growing scope.
• Hands-on dbt for transformation and testing at scale.
• Strong SQL and Python for data pipelines.
• Experience with enterprise data models and governance.

Responsibilities

• Own the analytics platform roadmap and governance.
• Lead end-to-end data pipelines from ingestion to BI delivery.
• Mentor Analytics Engineer and Data Scientist.
• Define semantic layer and executive dashboards.

Skills

Analytics engineering

Data governance

SQL

Python

dbt

Snowflake

AWS

Data modeling

Education

Bachelor's degree in CS or related field

Tools

Terraform

CloudFormation

dbt

Snowflake

AWS Glue

Step Functions

S3

Lambda

Job description

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 technical product or platform roadmap
• Demonstrated ability to manage competing stakeholder priorities and communicate platform trade-offs to senior leadership

Preferred

• Experience in the life insurance or annuities industry strongly preferred; broader financial services considered
• Experience with life
• Exposure to actuarial data workflows or direct experience supporting actuarial teams
• Experience with data observability tools (Monte Carlo, Great Expectations, dbt tests, etc.)
• Experience with Git-based version control and CI/CD workflows for data pipelines
• Experience working with distributed compute frameworks (e.g., Spark via AWS Glue or EMR)
• Familiarity with SOC 2 Type II control frameworks and evidence collection practices
• Exposure to HIPAA requirements as they relate to underwriting or health-adjacent data
• Familiarity with CCPA/CPRA and multi-state data breach notification obligations
• Experience transitioning work from external vendors or consultancies to in-house
• Exposure to AI/ML pipeline patterns or feature engineering in support of modeling teams

Competencies

• Platform ownership mindset — you think in systems, not tickets, and take accountability for the health of the entire data platform
• Strong analytical mindset with high attention to detail and a zero-tolerance attitude toward data quality issues
• Excellent written and verbal communication skills — able to translate complex platform trade-offs and technical concepts for senior non-technical stakeholders
• Natural collaborator with experience working across engineering, business, actuarial, and compliance teams
• Self-directed with the ability to manage competing priorities and drive clarity in ambiguous, fast-paced environments
• A continuous improvement mindset — you're never satisfied with "good enough" and actively look for ways to raise the bar
• Comfortable acting as a technical mentor and setting standards for more junior team members

At Everly, wecelebrate our diverse backgrounds and support our differences, and we are dedicated to equal employment opportunities regardless of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or any other legally protected status.

We’re also committed to adding new perspectives to our team and invite applications from people of all walks of life. We understand that experience comes in many forms, so if you believe you’re close to what we’re looking for, please consider applying.

Everly offers a competitive salary and as a full-time employee you are eligible for our robust benefits package including:

• Employees are eligible for an annual incentive bonus designed to reward for performance.
• The salary range for this job in most geographic locations in the US is $130,000 to $152,000

◦ Candidates hired to work in other locations will be subject to the pay range associated with that location and will be reflected in the candidate’s offer letter.

• Flexible paid time off for PTO, plus paid holidays, days of Significance, and a Volunteer Day
• Paid parental leave eligible after 3 months of service
• Medical, Dental & Vision Insurance
• 401k with company match
• Profit Sharing & Savings Plan
• Short-term and long-term disability insurance
• Flexible spending account
• Life insurance
• Educational Assistance
• Associate Assistance Programs and more!

Visit the career section to apply and submit your resume. EOE

Originally posted on Himalayas