Staff Data Engineer

Grubhub (Wonder) is hiring a Staff Data Engineer to provide hands-on technical leadership across core data systems and domain data products. The role owns end-to-end architecture for connected pipelines and data products, sets standards across engineering teams, and mentors engineers while partnering with product, analytics, and platform stakeholders to deliver trusted datasets.

Location and Compensation

• Location: New York, NY (onsite)
• Base Salary (New York): USD 208,500 - 225,000 per year
• Base Salary (Illinois): USD 187,500 - 202,500

Wonder uses geographic-specific salary structures, so the final offer may vary based on candidate skills, education, training, credentials, and experience.

Core Responsibilities

• Own the architecture of critical data pipelines and domain data products from ingestion through transformation, modeling, and serving, making cross-system design calls.
• Set technical direction and standards for data engineering across multiple teams, including data modeling, CI/CD automated testing, data validation, data observability, and SLOs for tier-1 datasets.
• Develop performant, concise, and secure code for complex and business-critical problems; lead design and code reviews beyond your own team.
• Partner with product, analytics, and platform teams to standardize metrics and publish trusted golden datasets for reporting, experimentation, and ad-hoc analysis.
• Identify and manage technical debt, cost inefficiency, and reliability risk across the data stack before issues become urgent.
• Evaluate new technologies and architectural patterns rigorously, adopting approaches that fit scale and needs while rejecting those that do not.
• Mentor senior and mid-level engineers and participate in hiring, improving team technical depth so critical systems are not dependent on a single person.
• Translate technical trade-offs into business terms for stakeholders up to leadership and document design rationale so decisions endure beyond team changes.
• Educate others and promote data engineering best practices to build a strong data culture across the engineering organization.

Required Qualifications

• Bachelor's Degree in a science, programming, or engineering related field, or equivalent experience
• 6+ years of experience in data engineering with a strong foundation in distributed systems and software engineering
• Deep expertise in dimensional data modeling (star/snowflake schemas, fact and dimension design, slowly changing dimensions) and in building reusable, well-governed data products for analytics at scale
• Advanced SQL and hands-on experience with large-scale distributed processing frameworks including Spark (PySpark/Spark SQL), Hive, Trino, and Flink, including performance tuning and cost optimization of large workloads with high uptimes
• Multi-cloud data platform experience across AWS (S3, EMR) and GCP (BigQuery, GCS, Dataproc), including highly valued experience migrating pipelines and warehouses to GCP/BigQuery
• Experience building batch and streaming pipelines with workflow orchestration tools such as Airflow and Azkaban, with a strong interest in event-driven architecture
• Strong data quality engineering practices including CI/CD automated testing, data validation, data observability, and data privacy
• Solid software engineering fundamentals: Python (Java/Scala a plus), data structures and algorithms, clean and testable code, and code reviews
• Proven staff-level technical leadership across teams or systems, driving architecture reviews beyond your own team and influencing decisions without direct authority
• Clear communication with technical and non-technical audiences, including executive stakeholders
• Pragmatism with a consistent focus on software quality and engineering standards

Technologies

• SQL, Spark, PySpark, Spark SQL, Hive, Trino, Flink
• Python, Java, Scala
• AWS, S3, EMR
• GCP, BigQuery, GCS, Dataproc
• Airflow, Azkaban

Benefits

• Competitive compensation package with equity
• 401(k)
• Choice of medical, dental, and vision plans
• Company-paid short and long term disability coverage
• Paid time off, including flexible time off for exempt employees
• Paid vacation for non-exempt employees
• Paid sick leave in compliance with applicable law
• Paid parental leave
• Discounted meals
• Exclusive perks across the Wonder family of brands

Additional Experience (Valued)

• Finance and accounting domain experience, including pipelines for orders, payments, and accounting in partnership with FP&A and Accounting to define and certify financial metrics (e.g., GMV, net revenue)
• Reconciliation pipelines (order to payment to ledger) supporting month-end close, revenue, and accruals
• SOX-compliant data pipelines, including change management, access controls, data lineage, and auditability

Employment Notices

• Wonder participates in the federal government’s E-Verify program to confirm employment eligibility.
• If you need an accommodation during the interview process, inform your recruiter.