Staff Software Engineer, Data Lake Ingestion

Join a leading fintech company that’s democratizing finance for all.

Robinhood Markets was founded on a simple idea: that our financial markets should be accessible to all. With customers at the heart of our decisions, Robinhood and its subsidiaries and affiliates are lowering barriers and providing greater access to financial information. Together, we are building products and services that help create a financial system everyone can participate in.

With growth as the top priority...

The business is seeking curious, growth-minded thinkers to help shape our vision, structures and systems; playing a key-role as we launch into our ambitious future. If you’re invigorated by our mission, values, and drive to change the world — we’d love to have you apply.

About the team + role

Our team's mission at Robinhood is to empower informed decision-making, foster innovation, and drive organizational excellence through a reliable, timely, efficient, and privacy-aware Data Lake and Ingestion Infrastructure.

As a Staff Software Engineer, you will lead the development of data ingestion pipelines that process petabytes of data and billions of events daily. This role is highly cross-functional, requiring you to collaborate closely with Data Science, Data Engineering, and Product teams to understand customer requirements, and with Data Platform and Storage teams to develop integrated solutions. We extensively utilize open-source frameworks as the foundation for our platforms.

It is preferred that this role is located in one of the office locations listed on this job description which will align with our in-office working environment. This position is only eligible for remote work in limited geographies within the US where we do not have physical office locations. Please connect with your recruiter for more information regarding our in-office philosophy and expectations.

What you’ll do

• Partner to influence and shape the vision, strategy, and adoption of current and future technologies.
• Design, build, and maintain efficient and reliable batch and streaming data pipelines that drive key data insights across the Robinhood family of products.
• Lead initiatives to improve data quality, efficiency, and privacy at scale.
• Forge trusting cross-functional partnerships with data producers and consumers across Robinhood to ensure our solutions meet their needs.
• Establish best practices and standards for data operations and lifecycle management.
• Mentor engineers at Robinhood, both formally and informally.

What you bring

• 6+ years of experience as a proven staff engineer with expertise in planning and leading large projects, specifically focused on data infrastructure.
• Proficiency in a comprehensive range of data engineering disciplines, including data and stream processing technologies (e.g., Spark, Flink, Kafka, Hudi), data serialization formats (e.g., Avro, Protobuf), workflow orchestration tools (e.g., Airflow), and Data Stores (e.g., Postgres, ClickHouse, Redis).
• Strong coding skills in Python, Java, Go or similar languages.
• Experience with at least one major cloud suite of offerings (AWS, GCP, Azure).
• Proven experience in contributing to open-source technologies such as Spark, Hudi, Flink, Kafka etc.

What we offer

• Market competitive and pay equity-focused compensation structure
• 100% paid health insurance for employees with 90% coverage for dependents
• Annual lifestyle wallet for personal wellness, learning and development, and more!
• 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!
• Lively office environment with catered meals, fully stocked kitchens, and geo-specific commuter benefits

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on September 19, 2024.

Please see the independent bias audit report covering our use of Covey here.

Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected salary range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. This role is also eligible to participate in a Robinhood bonus plan and Robinhood’s equity plan. For other locations not listed, compensation can be discussed with your recruiter during the interview process.

Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)$217,000—$255,000 USDZone 2 (Denver, CO; Westlake, TX; Chicago, IL)$190,000—$224,000 USDZone 3 (Lake Mary, FL)$169,000—$199,000 USD

Click here to learn more about available Benefits, which vary by region and Robinhood entity.

We’re looking for more growth-minded and collaborative people to be a part of our journey in democratizing finance for all. If you’re ready to give 100% in helping us achieve our mission—we’d love to have you apply even if you feel unsure about whether you meet every single requirement in this posting. At Robinhood, we're looking for people invigorated by our mission, values, and drive to change the world, not just those who simply check off all the boxes.

Robinhood embraces a diversity of backgrounds and experiences and provides equal opportunity for all applicants and employees. We are dedicated to building a company that represents a variety of backgrounds, perspectives, and skills. We believe that the more inclusive we are, the better our work (and work environment) will be for everyone. Additionally, Robinhood provides reasonable accommodations for candidates on request and respects applicants' privacy rights. Please review the specific Robinhood Privacy Policy applicable to the country where you are applying.