Equity Residential is looking to advance its analytical and data science capabilities by building, unifying, and scaling internal products that transform analytical insights into operational decision tools.
Requirements
- Proficiency in modern web frameworks (e.g., React, Vue, or similar) and backend frameworks (e.g., FastAPI, Flask, or similar Python-based systems).
- Strong command of Python and JavaScript/TypeScript.
- Experience developing APIs and microservices within cloud environments (Azure preferred).
- Familiarity with data-oriented technologies such as Snowflake, Databricks, or similar platforms is a plus
- Experience with CI/CD pipelines, containerization, and cloud-native deployment.
- Proven ability to design and maintain secure, reliable, and scalable systems.
- Demonstrated leadership in technical mentorship and architecture design.
Responsibilities
- Lead the design and implementation* of scalable, maintainable web applications that operationalize data science and analytics products.
- Define technical architecture and standards for front-end and back-end systems* supporting data products and analytical tools.
- Collaborate with data scientists, analysts, and business stakeholders* to translate analytical models into usable, intuitive applications.
- Develop APIs and application services that integrate with core data platforms* (Snowflake, Databricks, Azure) and operational systems.
- Establish best practices for code quality*, CI/CD, and secure deployment of production systems.
- Mentor data engineers and other technical contributors* in full-stack development, software design, and product engineering principles.
- Partner with cloud and enterprise engineering teams* to ensure applications are performant, reliable, and cost-effective at scale.
Other
- Our current onsite work schedule requires attendance from Monday through Thursday each week, with remote work permitted on Fridays.
- A Product-Minded Builder: You love turning ideas into polished, reliable applications. You thrive in ambiguous environments where the path isn’t fully defined, and you enjoy shaping engineering structure out of complexity.
- User-Centered and Business-Aware: You care about the “why” behind what you build. You ask sharp questions, seek to understand the workflows and pain points of end users, and shape features that clearly tie back to the business outcome.
- Collaborative and Supportive: You work well with data scientists, data engineers, and analysts to operationalize models and insights. You communicate clearly, share knowledge freely, and help elevate the team’s engineering maturity through mentorship and constructive design discussions.
- Effective communication and collaboration skills, with the ability to work across data, engineering, and business teams.
