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Data Analyst

  • Hybrid
    • Boston, Massachusetts, United States

Job description

Location: Boston, MA (Full-Time, Hybrid, 4 days a week in the office) 
Reports to: Chief Operations Officer (COO) 

Entyre Care 

Our Mission 

Serve Families. Our Method: Relentless Speed. 
Entyre Care radically supports family caregivers with financial, emotional, and expert resources. We operate with urgency, focus, and a commitment to delivering “insanely great” outcomes for families. 

Your Responsibilities

  • Develop and optimize SQL queries in Databricks for daily reports and forecasts

  • Analyze operational data to identify trends, bottlenecks, and potential improvements

  • Automate data processes using Python

  • Work closely with the stakeholders

  • Continuously improve service and process quality through data-driven transparency and a focus on what truly matters

How We Operate – Non-Negotiable 

  • “Insanely Great” for Families – Delivered Now: 
    Relentlessly solve caregiver needs with excellence and speed. 

  • Speed is King – Ruthless Focus: 
    Eliminate distractions and execute on critical objectives with urgency. 

  • Raise the Bar: 
    Demand A-player performance and continuous improvement from yourself and your team. 

  • The Speed Algorithm: 
    Question, delete, simplify, and accelerate every process. Remove bottlenecks and friction. 

  • Act Like Owners – Bold Bets, Fast Action: 
    Take initiative, make bold decisions, and move fast to drive results for families. 

The Bottom Line 

This is a high-impact, operational leadership role at the heart of a mission-driven company. If you are energized by building and optimizing finance operations at speed—and want to make a difference for millions of families—join us at Entyre Care. 

Job requirements

  • Strong knowledge of SQL and experience with Databricks SQL or similar platforms

  • Solid Python skills, especially for data analysis and automation

  • Basic understanding of relational databases and handling of structured data

  • Initial experience with data (through work, studies, or projects) – motivated career starters are welcome

  • Ideally, experience with time series, forecasting, or KPI tracking

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