Stripe is hiring a Staff Software Engineer, Data Engineering Solutions in 8122 Data Foundations — Bengaluru. The overview below is synthesized from the employer posting on stripe.com: factual requirements and scope are preserved, but prose is rewritten with editorial context. Verify details and apply via the employer link.
Who we are
About Stripe
Company context from the listing:
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.
About the team
Company context from the listing:
We're experts in data, working to make it cost-effective, understandable, and trustworthy. We build pipelines processing billions of events a day and are stewards of canonical data warehouses and datasets delivering products for Stripe Users while embedding with teams to build their data products.
What you'll do
Day-to-day scope for the Staff Software Engineer, Data Engineering Solutions as described in the posting:
The listing frames the Staff Software Engineer, Data Engineering Solutions at Stripe as a hands-on product role. The ideal candidate is someone who has built data pipelines for large-scale volume, is deeply knowledgeable of Data Engineering tools including Airflow, Spark, Kafka, and Flink, is empathetic, excels at building strong relationships, and collaborates effectively with other Stripe teams to understand their use cases and unlock new capabilities.
- Lead the technical outcomes for a team of ambitious, talented engineers, providing mentorship, guidance, and support to ensure their success
- Partner with our recruiting team to attract and hire top talent.
- Deliver cutting-edge data pipelines that scale to users' needs, focusing on reliability and efficiency
- Develop strong subject matter expertise and manage the SLAs of data pipelines and full-stack web applications that support critical stakeholders
- Collaborate with product managers and peers across the company to create and improve canonical datasets and data warehouses, use golden paths, and ensure Stripe employees and customers are using trustworthy data
- Leverage AI, LLM, and Agents at scale to produce and analyze high-quality data on ambiguous problems
- Have an opportunity to work with Spark, Flink, Kafka, Trino, Pinot, Airflow, Scala, Java, SQL, and Python, and many other big data technologies
- Have the opportunity to drive the execution of key data initiatives for Stripe, overseeing the entire development lifecycle from planning to delivery while maintaining high standards of quality and timely completion
- Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team
Who you are
Experience and skills the team lists as required:
The listing frames the Staff Software Engineer, Data Engineering Solutions at Stripe as a hands-on product role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements
Experience and skills the team lists as required:
- 10+ years of engineering experience with 5+ years of hands-on experience building and operating data systems and pipelines, datasets and data warehouses, infrastructure, and leading small teams to deliver excellent solutions
- A strong engineering background and passion for data
- Prior experience with writing and debugging data pipelines using a distributed data framework (Spark, Hadoop, Trino, etc.)
- An inquisitive nature in diving into data inconsistencies to pinpoint issues, and resolve deep-rooted data quality issues
- Knowledge of a backend development language (such as Scala, Java, or Go) and strong SQL experience
- Strong customer focus, with a commitment to partnering with Product Managers, leaders, and other Stripe engineers to understand their use cases
- Effective cross-functional collaboration, with the ability to think rigorously, communicate clearly, and make or coordinate difficult decisions and trade-offs
- Thrive with high autonomy and responsibility in an ambiguous environment
- Ability to foster and work in a healthy, inclusive, challenging, and supportive work environment
Preferred qualifications
Experience and skills the team lists as required:
- Expertise in Iceberg, Kafka, Change Data Capture, Flink, Spark, Airflow, Hive Metastore, Pinot, Trino, and AWS Cloud, and experience influencing open-source contributions
- Experience creating and maintaining Data Marts and Data Warehouses to power business reporting needs
- Experience working with Product or Go-to-Market (GTM—Sales and Marketing) teams
- Genuine enjoyment of innovation and a deep interest in understanding how things work, with the ability to question and direct architectural decisions
- Strong written and verbal communication skills for various audiences, including leadership, users, and company-wide stakeholders