This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Data Engineer based in United States.
This is a senior technical leadership role focused on designing and evolving modern, scalable data platforms.
You will shape core lakehouse architecture, data governance, metadata, security, and platform reliability.
The role combines hands-on engineering with architectural leadership across complex, cross-functional initiatives.
You will partner closely with Product, Analytics, Data Science, Security, and Platform teams to enable trusted data at scale.
Your work will support analytics, product capabilities, and AI systems through reliable and well-governed data foundations.
You will also act as a force multiplier by mentoring engineers and establishing technical standards that improve how teams build.
This is an opportunity to influence long-term data strategy while remaining deeply involved in practical engineering and delivery.
Accountabilities
- Design and evolve an Iceberg-based lakehouse architecture with a focus on scalability, performance, cost efficiency, and maintainability.
- Establish technical standards for table design, partitioning, schema evolution, optimization, and data layout across the data platform.
- Lead complex architectural initiatives spanning batch, streaming, and event-driven data processing, enabling teams to deliver independently within clear technical guardrails.
- Evaluate build-versus-buy decisions and assess emerging technologies to strengthen the data ecosystem.
- Define and implement shared approaches for metadata, dataset documentation, data lineage, governance, and cataloging using open standards and tools.
- Establish metadata practices that support self-service analytics, governance, and AI readiness while ensuring data models align with business terminology.
- Design and evolve secure data access models, including table-, column-, and row-level controls, and collaborate with Security and Platform teams on scalable policy enforcement.
- Build automation for compaction, retention, lifecycle management, and cost optimization while establishing observability standards for pipeline health, data quality, and reliability.
- Provide architectural leadership during critical incidents, identify systemic improvements, and reduce ongoing operational workload.
- Participate in architecture and design reviews, communicate complex technical concepts clearly, and align data initiatives with business and customer outcomes.
- Mentor senior and mid-level engineers, provide technical guidance, and raise engineering quality across the broader organization.
Requirements
- Bachelor’s degree in Computer Science or equivalent professional experience, with typically 12+ years of experience building and operating large-scale data systems.
- Deep expertise in distributed data systems, data architecture, and the design of secure and governed data platforms.
- Strong hands-on experience with Apache Iceberg or comparable table formats such as Delta Lake or Hudi.
- Advanced proficiency in Python and SQL, along with experience designing data orchestration patterns using tools such as Airflow.
- Experience with metadata, data catalogs, governance frameworks, and broader modern data ecosystems.
- Strong experience working in at least one major cloud environment, such as AWS, GCP, or Azure, including cloud-native data services and object-storage-based lakehouses.
- Familiarity with infrastructure-as-code and automated platform management.
- Strong understanding of batch, streaming, and event-driven architectures, as well as data security, access control, privacy, and compliance considerations.
- Proven ability to operate as a senior technical leader, set architectural direction, influence cross-functional teams, and mentor other engineers.
- Excellent written and verbal communication skills, with the ability to translate complex technical concepts for engineering, product, analytics, security, and data science stakeholders.
- Permanent authorization to work in the United States is required.
Benefits
- Base salary ranging from $175,000 to $218,000 USD, depending on experience, skills, certifications, education, and other relevant factors.
- Eligibility for a potential annual bonus of up to 10% based on company performance.
- Equity opportunities through a common share option grant with a defined vesting schedule.
- Comprehensive health benefits, including a no-monthly-cost medical plan.
- Fully paid parental leave of 5 or 13 weeks.
- 401(k) matching at 100% for the first 3% contributed and 50% from 3–5%.
- Flexible time-away benefits, including PTO, sick time, volunteer time, and seven paid holidays annually.
- Annual funds supporting an active lifestyle and opportunities to participate in company-wide outdoor activities.
- Opportunities for professional growth, technical leadership, and meaningful impact within a mission-driven environment.
- Flexible work options through established distributed-work communities, offices, and virtual workforce hubs across eligible U.S. locations.
- Commitment to an inclusive workplace, equal opportunity, reasonable accommodations, and a culture that values diverse perspectives.
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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