What are the responsibilities and job description for the Technical Lead - Data Engineering position at Robinhood Financial?
Our team is responsible for building and maintaining the foundational datasets that power decision-making at Robinhood. We're a fast-paced team in a fast-growing company, and we're seeking a Senior Data Engineer to help us lay the groundwork for reliable, impactful data-driven decisions across the organization.
This is a unique opportunity to work on cutting-edge projects that drive innovation and growth. As a member of our team, you'll have the chance to collaborate with experts from various fields, including engineering, data science, and business, to deliver high-quality solutions that meet our customers' needs. Your contributions will have a direct impact on our products and services, enabling us to better serve our users and stay ahead of the competition.
**Key Responsibilities:**
- Help define and build key datasets across all Robinhood product areas
- Lead the evolution of these datasets as use cases grow
- Build scalable data pipelines using Python, Spark, and Airflow to move data from different applications into our data lake
- Partner with upstream engineering teams to enhance data generation patterns
- Collaborate with data consumers across Robinhood to understand consumption patterns and design intuitive data models
- Code and develop tools for data engineering and standards
- Define and promote data engineering best practices across the company
**Requirements:**
- 5 years of professional experience building end-to-end data pipelines
- Proven ability to implement software engineering-caliber code (preferably Python)
- Expertise in building and maintaining large-scale data pipelines using open-source frameworks (Spark, Flink, etc.)
- Strong SQL skills (Presto, Spark SQL, etc.)
- Experience solving problems across the data stack (Data Infrastructure, Analytics, and Visualization platforms)
- Expert collaborator with the ability to democratize data through actionable insights and solutions
- Experience building data engineering tools and pipelines for Experimentation and A/B Testing is a strong plus
**Benefits:**
- Market-competitive compensation structure with pay equity focus
- 100% paid health insurance for employees with 90% coverage for dependents
- Annual lifestyle wallet for personal wellness, learning, and development
- Lifetime maximum benefit for family forming and fertility benefits
- Dedicated mental health support for employees and eligible dependents
- Generous time away including company holidays, paid time off, sick time, parental leave, and more
This is a unique opportunity to work on cutting-edge projects that drive innovation and growth. As a member of our team, you'll have the chance to collaborate with experts from various fields, including engineering, data science, and business, to deliver high-quality solutions that meet our customers' needs. Your contributions will have a direct impact on our products and services, enabling us to better serve our users and stay ahead of the competition.
**Key Responsibilities:**
- Help define and build key datasets across all Robinhood product areas
- Lead the evolution of these datasets as use cases grow
- Build scalable data pipelines using Python, Spark, and Airflow to move data from different applications into our data lake
- Partner with upstream engineering teams to enhance data generation patterns
- Collaborate with data consumers across Robinhood to understand consumption patterns and design intuitive data models
- Code and develop tools for data engineering and standards
- Define and promote data engineering best practices across the company
**Requirements:**
- 5 years of professional experience building end-to-end data pipelines
- Proven ability to implement software engineering-caliber code (preferably Python)
- Expertise in building and maintaining large-scale data pipelines using open-source frameworks (Spark, Flink, etc.)
- Strong SQL skills (Presto, Spark SQL, etc.)
- Experience solving problems across the data stack (Data Infrastructure, Analytics, and Visualization platforms)
- Expert collaborator with the ability to democratize data through actionable insights and solutions
- Experience building data engineering tools and pipelines for Experimentation and A/B Testing is a strong plus
**Benefits:**
- Market-competitive compensation structure with pay equity focus
- 100% paid health insurance for employees with 90% coverage for dependents
- Annual lifestyle wallet for personal wellness, learning, and development
- Lifetime maximum benefit for family forming and fertility benefits
- Dedicated mental health support for employees and eligible dependents
- Generous time away including company holidays, paid time off, sick time, parental leave, and more
