Strategic Overview
Software Engineer, Data Orchestration at Stripe is a dev opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as Design, build, and maintain next-generation and first-generation versions of key Data Platform products, with an emphasis on usability, reliability, security, and efficiency. Design ergonomic APIs and abstractions that build a great customer experience for…
The role is listed for N / A with the working arrangement published with the role, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
The Big Data Infrastructure operates the critical infrastructure that powers the batch data processing at Stripe. The team supports a variety of use cases, including Payment, Ledger, ML, Fraud Detection, Product Analytics, Regulatory Reporting, Financial Data Reconciliation, and externally facing products like Radar and Sigma. As an example of the scale, the team's systems serve hundreds of teams, thousands of…
Data Orchestration builds and operates the time-based and event-based orchestration infrastructure that powers and accelerates batch data pipelines. The team operates on a wide range of tech stacks including Airflow, Spark, SQL, Kafka, Flink, Hive MetaStore, Trino, Pinot, Python, Java, Scala, S3, and Iceberg.
Key Responsibilities & Objectives
- Design, build, and maintain next-generation and first-generation versions of key Data Platform products, with an emphasis on usability, reliability, security, and efficiency.
- Design ergonomic APIs and abstractions that build a great customer experience for internal Stripes, that will in turn enhance the experience of millions of Stripe users.
- Ensure operational excellence and enable a highly available and reliable Data Orchestration platform across batch workloads.
- Collaborate with high-visibility teams and their stakeholders to support their key initiatives—while building a robust platform that benefits all of Stripe in the long term.
Required Qualifications & Candidate Blueprint
- 8+ years of professional experience writing high-quality, production-level code or software programs and an interest in data infrastructure.
- Has experience operating or enabling large-scale, high-availability data pipelines from design to execution and safe change management. Expertise in Spark, Flink, Airflow, Python, Java, SQL, and API design is a plus.
- Has experience developing, maintaining, and debugging distributed systems built with open source tools.
Salary & Benefits
The available source data does not publish a numerical salary range for this opening. We do not estimate or substitute third-party figures.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
Who we are
About Stripe
Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.
About the team
The Big Data Infrastructure operates the critical infrastructure that powers the batch data processing at Stripe. The team supports a variety of use cases, including Payment, Ledger, ML, Fraud Detection, Product Analytics, Regulatory Reporting, Financial Data Reconciliation, and externally facing products like Radar and Sigma. As an example of the scale, the team's systems serve hundreds of teams, thousands of workflows, 100,000+ task executions, O(billion) transformations, and moving terabytes of data processing over 1 GB/second every day. Our users inside Stripe include other engineering teams, Data Scientists, Sales and Operations, Finance, etc.
Data Orchestration builds and operates the time-based and event-based orchestration infrastructure that powers and accelerates batch data pipelines. The team operates on a wide range of tech stacks including Airflow, Spark, SQL, Kafka, Flink, Hive MetaStore, Trino, Pinot, Python, Java, Scala, S3, and Iceberg.
What you'll do
As a Software Engineer on this team, you'll design and build infrastructure that powers batch data processing at Stripe.
Responsibilities
- Design, build, and maintain next-generation and first-generation versions of key Data Platform products, with an emphasis on usability, reliability, security, and efficiency.
- Design ergonomic APIs and abstractions that build a great customer experience for internal Stripes, that will in turn enhance the experience of millions of Stripe users.
- Ensure operational excellence and enable a highly available and reliable Data Orchestration platform across batch workloads.
- Collaborate with high-visibility teams and their stakeholders to support their key initiatives—while building a robust platform that benefits all of Stripe in the long term.
- Plan for the growth of Stripe infrastructure by unblocking, supporting, and communicating with internal partners to achieve results.
- Connect your work with improvements in the usability and reliability of open source software (OSS) like Apache Airflow, Iceberg, and Spark, and contribute back to the OSS community.
Who you are
We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements
- 8+ years of professional experience writing high-quality, production-level code or software programs and an interest in data infrastructure.
- Has experience operating or enabling large-scale, high-availability data pipelines from design to execution and safe change management. Expertise in Spark, Flink, Airflow, Python, Java, SQL, and API design is a plus.
- Has experience developing, maintaining, and debugging distributed systems built with open source tools.
- Has experience building infrastructure-as-a-product with a strong focus on user needs.
- Has strong collaboration and communication skills, and can interact with both technical and non-technical participants.
- Has the curiosity to learn about new technologies and business processes.
- Is energized by delivering effective, user-first solutions through creative problem-solving and collaboration.
Preferred qualifications
- Has experience writing production-level code in Scala, Spark, Flink, Airflow, Python, Java, and SQL.
- Has experience designing APIs or building developer platforms.
- Has experience optimizing the end-to-end performance of distributed systems.
- Has experience scaling distributed systems in a fast-moving environment.
- Has experience working with Airflow infrastructure.
- Genuine enjoyment of innovation and an interest in understanding how things work.
Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users. This hits a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for individuals and their teams.
Office location—Bengaluru, KA, India
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This dev opening is a useful opportunity for candidates whose experience matches the role-specific capabilities named in the listing. Its strongest career signal is the scope of the work itself — particularly Design, build, and maintain next-generation and first-generation versions of key Data Platform products, with an emphasis on usability, reliability, security, and efficiency. — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground the role-specific capabilities named in the listing, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
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