Staff Data Engineer

Grubhub Holdings Inc.; New York (NY); On-site; USD 209,000 - 225,000; Full time

Benefits offered by this job

401(k)

Equity

Medical, dental, vision plans

Paid time off

Parental leave

Disability coverage

Discounted meals

Wonder perks

Job summary

Grubhub Holdings Inc. is seeking a Staff Data Engineer to shape core data systems and domain data products with technical leadership.

You will own end-to-end pipelines, set engineering standards, and partner across teams to deliver trusted datasets for analytics and decision-making. You will mentor engineers, drive architectural decisions, and promote a strong data culture while collaborating with product, analytics, and platform teams across multi-cloud environments.

Qualifications

• Bachelor's degree in a science, programming, or engineering related field or equivalent experience.
• 6+ years of data engineering experience with distributed systems and software engineering.
• Deep expertise in dimensional data modeling (star/snowflake, slowly changing dimensions).
• Advanced SQL and experience with Spark, Hive, Trino, and Flink with performance tuning.
• Multi-cloud data platform experience across AWS and GCP; BigQuery/Dataproc valued.
• Experience building batch and streaming pipelines with Airflow and Azkaban.
• Strong data quality practices: CI/CD testing, validation, observability, privacy.
• Solid software fundamentals in Python/Java/Scala and code reviews.
• Staff-level leadership across multiple teams or systems.

Responsibilities

• Own architecture of critical data pipelines and domain data products end to end.
• Set data engineering standards across multiple teams including CI/CD, testing, and observability.
• Write performant, secure code for complex problems and lead reviews beyond your team.
• Partner with product and analytics to standardize metrics and publish golden datasets.
• Identify and manage technical debt, costs, and reliability risks across the data stack.
• Evaluate new technologies and patterns to fit company scale and needs.
• Mentor senior engineers, participate in hiring, and increase team depth.
• Translate trade-offs into business terms for leadership and document rationale.
• Promote best practices to build a strong data culture across engineering.

Skills

Distributed systems

Advanced SQL

Python

Data modeling

Spark / PySpark

Airflow

Code reviews

Leadership

Communication

Education

Bachelor's degree in related field

Tools

Spark (PySpark)

Hive

Trino

Flink

Airflow

Azkaban

Python

Java/Scala

AWS S3/EMR

BigQuery/GCS/Dataproc

Job description

As a Staff Data Engineer at Grubhub (Wonder), you will help shape and deliver core data systems and domain data products with hands-on technical leadership. The role focuses on end-to-end ownership of connected pipelines and data products, setting engineering standards across teams, and partnering to deliver trusted datasets for analytics and decision-making.

What you will work on

• Own the architecture of critical data pipelines and domain data products end to end, including ingestion, transformation, modeling, and serving, and make cross-system design decisions.
• Set technical direction and standards for data engineering across multiple teams, covering data modeling, CI/CD automated testing, data validation, data observability, and SLOs for tier-1 datasets.
• Write performant, concise, and secure code for the most complex, business-critical problems, and lead design and code reviews beyond your own team.
• Partner with product, analytics, and platform teams to standardize metrics and publish golden datasets used for reporting, experimentation, and ad-hoc analysis.
• Identify and proactively manage technical debt, cost inefficiencies, and reliability risks across the data stack before they escal.
• Evaluate new technologies and architectural patterns with rigor, adopting what fits the company’s scale and needs while rejecting approaches that do not.
• Mentor senior and mid-level engineers, participate in hiring, and help increase team depth so critical systems do not depend on a single person.
• Translate technical trade-offs into business terms for stakeholders up to leadership, and document design rationale so decisions remain clear over time.
• Educate others and promote data engineering best practices to build a strong data culture across engineering.

Experience and qualifications

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

Tools and technologies

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

Additional interests that are a plus

• 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 (for example, GMV and net revenue).
• Reconciliation pipelines supporting month-end close, revenue, and accruals (order to payment to ledger).
• SOX-compliant data pipelines covering change management, access controls, data lineage, and auditability.

Compensation and benefits

• Base salary: New York $208,500 - $225,000 (geographic-specific salary structures apply).
• 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, plus 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.

Location and eligibility

• Location: New York, NY (onsite).
• Wonder participates in the federal government's E-Verify program to confirm employment eligibility.
• If you need an accommodation during the interview process, let your recruiter know.