Staff Software Engineer, Data Engineering Solutions

United States Digital Space LLC; Seattle (WA); On-site; USD 130,000 - 160,000; Full time

Benefits offered by this job

Innovative work environment

Collaboration opportunities

Job summary

United States Digital Space LLC is seeking a Staff-level Data Engineer to lead solutions for high-impact data challenges. The ideal candidate will have over 10 years of experience in building data systems and pipelines, with strong knowledge of tools like Airflow, Spark, and Kafka.

The role involves mentoring engineers, collaborating with product teams, and enabling the creation of trustworthy data pipelines. A commitment to customer focus and strong problem-solving skills are essential for this position.

Qualifications

• Minimum of 10 years experience building and operating data systems.
• Strong engineering background with data pipelines.
• Knowledge of backend languages and SQL proficiency.

Responsibilities

• Lead the technical outcomes for a team of engineers.
• Deliver cutting-edge data pipelines focusing on reliability.
• Collaborate with product managers to improve datasets.

Skills

Data Engineering

Building Data Pipelines

Collaboration

Customer Focus

Problem-Solving

SQL

Education

10+ years of experience in data systems

Tools

Airflow

Spark

Kafka

Flink

Scala/Java/Go

Job description

Who we are

About the company

the company is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use the company 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

We are 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 the company Users while embedding with teams to build their data products. We are experts in using the the company Data Platform and to scale we lead the data culture and data education to enable product teams to own their data. We invest in AI-driven Data Ops to scale incident handling and serve as an escalation path for data incidents to minimize their impact. The Data Engineering Solutions team will work closely with product teams delivering trustworthy data / backend code / and innovative AI tools/platforms/services for data.

What you’ll do

We're looking for a person who could drive the Data Engineering Solutions team in solving high-impact, cutting-edge data problems. The ideal candidate will be someone that has built data pipelines for large scale volume, is deeply knowledgeable of key tools including Airflow/Spark/Kafka/Flink, is empathetic, excels at building strong relationships, and collaborates effectively with other the company teams to understand their use cases and unlock new capabilities.

Responsibilities

• 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/improve canonical datasets and data warehouses, use golden paths, and ensure Stripes and customers are using trustworthy data
• Leverage AI/LLM and Agents at scale to produce and analyze high-quality data on ambiguous problems
• Have the opportunity to drive the execution of key data initiatives for the company, 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

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

• This is a Staff-level role — that typically means 10+ years of experience building and operating data systems, pipelines, warehouses, infrastructure, and leading teams to deliver exceptional solutions
• A strong engineering background and passion for data as well as prior experience with writing and debugging data pipelines using a distributed data framework
• 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
• Extreme customer focus, with a commitment to partnering with product, leaders across the business, and other the company 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

• Our stack is made up of Iceberg, Kafka, Change Data Capture, Flink, Spark, Airflow, Hive Metastore, Pinot, Trino, AWS Cloud - experience with all or some of these tools is a huge plus
• Influencing open-source contributions is a huge plus
• Experience creating and maintaining data marts / warehouses to power business reporting needs
• Experience collaborating with Product, Go-To-Market, or Sales / 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