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.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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