Analytics Engineer

Description:

Why Join Sensi.AI

Sensi is redefining how care organizations support aging at home by using it’s Care Intelligence platform to translate everyday signals into meaningful clinical and operational outcomes.

Sensi’s platform is deployed across 50 states in leading home-care providers, supporting tens of thousands of seniors aging safely at home. By transforming real-world activity in the home into actionable insights, Sensi enables care teams to detect changes in condition earlier, intervene proactively, and deliver higher-quality care at scale.

This is a hybrid role based in Tel- Aviv, Israel.

About the role

Sensi builds AI products for home care. We’re looking for a Analytics Engineer to own the data and analytics foundation that helps Product, Growth, Customer Success, R&D, and leadership make better decisions.

You’ll own the path from raw data to actionable insight - building reliable models, defining key metrics, analyzing product and business performance, and communicating what the data actually tells us.

What you'll do

• Own and improve our data models, pipelines, and analytics infrastructure
• Define and maintain core product and business metrics
• Partner with Product and Engineering on instrumentation and data quality
• Analyze product performance, customer behavior, funnels, retention, and business trends
• Evaluate product changes and experiments and provide statistically sound conclusions
• Build dashboards and analyses that help teams make better decisions
• Communicate insights clearly to both technical and non-technical stakeholders

• 4+ years of experience in product analytics, BI, data analytics, or analytics engineering
• Strong SQL and data modeling skills
• Experience with dbt or similar data transformation/modeling tools
• Experience working with different types of business and product data
• Experience with product analytics and BI tools, such as Mixpanel, Tableau, Power BI, or similar
• Strong analytical and statistical judgment, including working with experiments and imperfect data
• Strong ownership and communication skills, with the ability to turn data into clear, actionable recommendations

Nice to have

• Experience with modern data platforms and cloud technologies, such as AWS, Athena, Spark, or similar
• Experience with Python for analytics and data work
• Experience with AI, voice, or conversational products
• Experience in healthcare or home care