We are looking for a Staff Data Engineer to provide technical leadership across the core data systems and domain data products that power Grubhub's business. This is a hands-on technical leadership role. You will own the architecture of multiple connected pipelines and data products, and you will be accountable for how they fit together, not only for any single pipeline. You will set technical direction alongside other staff engineers, product managers and platform partners. You will raise the bar on how the organization builds, validates and operates data, and you will mentor the engineers around you through design reviews, code reviews and direct feedback.
The Impact You Will Make
Duties will include, but are not limited to
Own the architecture of critical data pipelines and domain data products end to end (ingestion, transformation, modeling and serving), and make the cross-system design calls.
Set technical direction and standards for data engineering across multiple teams: data modeling, CI/CD automated testing, data validation, data observability, SLOs for tier-1 datasets.
Write performant, concise and secure code on the most complex and 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 trusted golden datasets for reporting, experimentation and ad-hoc analysis.
Proactively find and manage technical debt, cost inefficiency and reliability risk across the data stack before they become urgent.
Evaluate new technologies and architectural patterns rigorously: adopt what actually fits our scale and needs, and say no to what does not.
Mentor senior and mid-level engineers, take part in hiring, and grow the team's technical depth so that no critical system depends on a single person.
Translate technical trade-offs into business terms for stakeholders up to leadership, and document design rationale clearly enough that decisions outlive the people who made them.
Educate others and promote data engineering best practices to build a strong data culture across the engineering organization.
What You Bring to the Table
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 designing reusable, well-governed data products for analytics 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 of large workloads with high uptimes.
Multi-cloud data platform experience across AWS (e.g. S3, EMR) and GCP (e.g. BigQuery, GCS, Dataproc). Experience migrating data pipelines and warehouses to GCP/BigQuery is highly valued.
Experience building batch and streaming pipelines with workflow orchestration tools (e.g. Airflow, Azkaban), and a 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 technical leadership at staff scope: setting technical direction across multiple teams or systems, driving architecture reviews beyond your own team, and influencing decisions without direct authority.
You communicate clearly with both technical and non-technical audiences, up to and including executive stakeholders.
You are pragmatic without compromising on software quality and standards.
Got These? Even Better
Finance and accounting domain experience: pipelines for orders, payments and accounting, built in partnership with FP&A, Accounting to define and certify financial metrics (e.g. GMV, net revenue).
Reconciliation pipelines (order to payment to ledger) that support month-end close, revenue and accruals.
SOX-compliant data pipelines: change management, access controls, data lineage and auditability.
New York Base Salary: $208,500 - $225,000.
Illinois Base Salary: $187,500 - $202,500.
Wonder uses geographic-specific salary structures, which means the salary offered may vary depending on where the job is located. The final salary offer will take into account various factors, such as the candidate's skills, education, training, credentials, and experience.
Benefits
The benefits applicable to this role include a competitive compensation package with equity and a 401(k). We also offer a 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, and paid sick leave in compliance with applicable law in addition to paid parental leave, discounted meals and exclusive perks across the Wonder family of brands.
Eligibility, effective dates, and available plan options vary by employment classification and location. To learn more about benefits for this role, visit our Careers page here.
A Final Note
At Wonder, we build the best teams by hiring with an objective lens — evaluating people for their potential while championing diversity, equity, and inclusion. We do not discriminate based on race, color, religion, gender identity or expression, sexual orientation, national origin, age, military service eligibility, veteran status, marital status, disability, or any other protected class. As part of our commitment to fair and compliant hiring practices, Wonder participates in the federal government's E-Verify program to confirm employment eligibility. If you need an accommodation during the interview process, please let your recruiter know.
We look forward to hearing from you! We'll contact you via email or text to schedule interviews and share information about your candidacy.
