Senior Data Engineer & Analyst

Evvy•New York City, NY

39d•Onsite

About The Position

Evvy is a precision women’s health company leveraging the vaginal microbiome to improve outcomes across a woman's lifespan. They have built the world’s largest dataset on the vaginal microbiome and an AI-powered personalized care platform. Evvy is seeking a Senior Data Engineer & Analyst to partner across their data ecosystem, acting as both a data engineer and an analyst. This role involves designing, building, and maintaining a modern data architecture to support critical decisions, self-service analytics, and data-driven innovation. The position is primarily in-person in New York, NY, and the ideal candidate is located in NYC.

Requirements

4-5 years of data analytics, analytics engineering, or data engineering experience at a startup.
Experience with ecommerce data and analytics (cohorting, waterfall visualization, LTV, retention, forecasting).
SQL wizard, Python experienced, data modelling expert, Git (version control) proficiency.
Experience with and opinions on current data stack: ETL tool like Stitch, Snowflake, DBT for data modelling, Metabase (or similar).
A deep understanding of the strengths and pitfalls of traditional BI teams.
Experience across the traditional BI setup, knowing when not to reinvent the wheel, but also when to break the mold.
AI-native by default and excited to integrate AI into Evvy’s data analytics workflows.
An owner and a self-starter who can see the big picture of how data serves the company’s mission and guide improvements proactively.
Strong written and verbal communication skills, able to work effectively with technical and non-technical teams.
Understanding of key business concepts and ability to frame analyses to answer business questions with guidance from non-technical teammates.

Nice To Haves

First or early data hire at an early stage startup.
Experience with HIPAA and working with sensitive health data.

Responsibilities

Own our data end-to-end, overseeing the entire data lifecycle from ingestion, transformation, data modelling, analysis, and reporting.
Collaborate with cross-functional teams to understand stakeholder questions and translate them into clear analytical workflows that inform decisions.
Develop our data infrastructure, including building and maintaining robust ETL pipelines, our data warehouse, and BI platform.
Explore, evaluate, and integrate AI & new data technologies to continuously improve data utilization.
Empower self-service analytics by partnering with business stakeholders to build intuitive data models.
Build out our semantic layer, defining and evolving shared data and context for AI tools.
Conduct advanced data analytics, from LTV and retention to lab operations and clinical treatment efficacy.
Establish data best practices, championing data governance, version control (Git), rigorous documentation, and organization.