Staff Software Engineer, Data Platform

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Software Engineer, Data Platform based in United States.

This role provides senior technical leadership across a modern data and AI platform, shaping the architecture, development, and operation of foundational data infrastructure. You will tackle company-wide technical challenges and influence how data and AI capabilities support business decision-making at scale. Working across multiple teams, you will combine hands-on engineering with architectural direction, technical strategy, and long-term platform planning. The role spans areas such as data pipelines, ETL frameworks, metrics platforms, infrastructure, data security, orchestration, and large-scale processing. You will also mentor engineers and help establish a culture of technical excellence, innovation, and strong engineering practices. This is a high-impact opportunity within a fast-moving environment focused on building scalable, reliable, and increasingly AI-ready data infrastructure.

Accountabilities:
- Provide technical leadership for the strategy, architecture, development, deployment, and operation of large-scale data and AI platforms.

- Identify and solve complex, organization-wide technical challenges through scalable and reliable data platform solutions.

- Establish architectural direction and technical standards while remaining hands-on in solving complex engineering and platform problems.

- Lead initiatives that span multiple teams, influence technology roadmaps, and translate technical strategy into measurable business outcomes.

- Drive best practices across data engineering and platform development, fostering a culture of craftsmanship, innovation, reliability, and continuous improvement.

- Provide technical leadership across ETL frameworks, metrics stores, infrastructure management, data security, and scalable data processing systems.

- Design, build, deploy, and maintain reliable multi-geographical data pipelines capable of operating at significant scale.

- Contribute to modern Lakehouse architecture patterns and the development of reusable platform components, high-performance services, and client libraries for big data workloads.

- Evaluate emerging technologies, conduct proofs of concept, and use research and technical analysis to guide architecture and technology decisions.

- Mentor engineers, scientists, and technical peers while supporting their professional development and strengthening the capabilities of the broader data platform organization.

- Collaborate effectively with engineering teams, technical stakeholders, leadership, and platform users to align technical priorities with business needs.

- Help evolve the broader data ecosystem toward infrastructure capable of supporting real-time analytics, AI/ML workloads, and agent-ready data experiences.

Requirements:

- Bring at least 8 years of experience in Data Platform engineering or an equivalent combination of professional and academic experience in a quantitative field.

- Demonstrate experience leading company-wide technical initiatives across multiple teams and influencing technology roadmap planning.

- Have a strong track record of collaborating with diverse technical and business stakeholders to deliver tangible outcomes.

- Demonstrate the ability to balance execution speed and operational delivery with deep technical research, statistical understanding, and scalable system design.

- Bring significant experience providing technical leadership on complex projects involving ETL frameworks, metrics stores, infrastructure, data security, and large-scale data processing.

- Have proven experience building, deploying, and maintaining reliable data pipelines across multiple geographic environments and at scale.

- Possess familiarity with workflow and orchestration technologies such as Airflow and dbt.

- Demonstrate hands-on experience designing modern Lakehouse data processing patterns.

- Bring experience with big data and cloud technologies such as GCP, Databricks, BigQuery, DataProc, Kafka, Kubernetes, Spark, DataFlow, Google Cloud Storage, and Airflow; experience across the full set is not required.

- Demonstrate strong written and verbal communication skills and the ability to explain complex technical concepts to engineers, leadership, users, and other diverse audiences.

- Be capable of rapidly evaluating technologies, conducting proofs of concept, and using findings to inform architecture and platform decisions.

- Demonstrate a strong mentoring mindset with experience investing in the technical and professional development of engineers, scientists, and peers.

- Be comfortable operating in complex, fast-paced environments where priorities and technical challenges may span multiple teams and domains.

Benefits:

- Full-time employment opportunity.

- Hybrid work arrangement based in Seattle, Washington; the source role is specifically based in Seattle.

- Base compensation range of $200,000–$260,000, depending on relevant experience, skills, qualifications, geographic considerations, internal equity, and market factors.

- Equity participation.

- Eligibility for bonus compensation.

- U.S.-based employees are eligible for medical, dental, and vision insurance.

- 401(k) plan.

- Short-term and long-term disability coverage.

- Basic life insurance.

- Well-being benefits.

- 20 paid vacation days per calendar year for U.S.-based employees.

- 12 paid company holidays per calendar year for U.S.-based employees.

- Additional compensation or benefits may apply depending on role, employment terms, and applicable requirements.