Staff Data Engineer

Staff Data Engineer role at Grubhub (Wonder) focused on hands-on technical leadership across core data systems and analytics data products.

Responsibilities

• Own the end-to-end architecture of critical data pipelines and domain data products, including ingestion, transformation, modeling, and serving
• Make cross-system design decisions across connected systems supporting data products
• Set technical direction and standards for data engineering across multiple teams (data modeling, CI/CD automated testing, data validation, data observability)
• Define and drive SLOs for tier-1 datasets
• Write performant, concise, and secure code for complex, business-critical problems
• Lead design and code reviews beyond your immediate 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 with rigorous standards, adopting what fits current scale and needs and rejecting what does not
• Mentor senior and mid-level engineers, participate in hiring, and strengthen team technical depth so critical systems do not depend on one person
• Translate technical trade-offs into business terms for stakeholders up to leadership
• Document design rationale clearly to preserve decision quality over time
• Educate teams and promote data engineering best practices to build a strong data culture across engineering

Requirements

• Bachelor's Degree in a science, programming, or engineering related field, or equivalent experience
• 6+ years of experience in data engineering with strong foundations in distributed systems and software engineering
• Deep expertise in dimensional data modeling (star/snowflake schemas, fact and dimension design, slowly changing dimensions)
• Experience designing 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
• Proven performance tuning and cost optimization for large workloads with high uptimes
• Multi-cloud data platform experience across AWS (S3, EMR) and GCP (BigQuery, GCS, Dataproc)
• Experience migrating data pipelines and warehouses to GCP/BigQuery is highly valued
• Experience building batch and streaming pipelines using workflow orchestration tools such as Airflow and Azkaban
• Passion for event-driven architecture
• Strong data quality engineering practices: 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
• Demonstrated staff-level technical leadership: setting direction across multiple teams or systems, driving architecture reviews beyond your team, and influencing decisions without direct authority
• Clear communication with both technical and non-technical audiences, including executive stakeholders
• Pragmatic approach that still upholds 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

Base Salary and Location

• Location: New York, NY (onsite)
• Base salary (New York): USD 208,500 - 225,000 per yearly
• Wonder uses geographic-specific salary structures; final offer may vary based on skills, education, training, credentials, and experience

Additional Information

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