Staff Data Engineer: Lead Data Platform (Equity)

Wonder; United States; Sur place; USD 188 000 - 225 000; Plein temps

Avantages offerts par ce poste

Equity

401(k)

Medical, dental & vision

Disability coverage

Paid time off & vacation

Parental leave

Discounted meals

Résumé du poste

Wonder is seeking a Staff Data Engineer to provide technical leadership across core data systems. You will own the architecture of multiple pipelines and data products, mentor engineers, and set standards for data modeling, testing, observability, and cost efficiency.

This is a hands‑on leadership role guiding teams toward scalable, reliable data solutions. New York and Chicago offices offer opportunities to collaborate with product, analytics, and platform teams while delivering trusted

Qualifications

• 6+ years in data engineering with distributed systems background.
• Advanced SQL with large-scale processing and performance tuning.
• Experience building batch/streaming pipelines and data products at scale.
• Proven leadership across multiple teams and data platforms.
• Strong communication with technical and executive stakeholders.

Responsabilités

• Own architecture of core data pipelines and domain data products end to end.
• Set data engineering standards across multiple teams (CI/CD, tests, observability).
• Write performant, secure code and lead design reviews beyond your team.
• Collaborate with product, analytics and platform teams to publish trusted datasets.
• Mentor engineers, participate in hiring, and grow technical depth.

Connaissances

Python

Spark

Hive

Trino

Flink

SQL

Airflow

CI/CD

Data modeling

Data quality

Observability

Multi-cloud AWS/GCP

Formation

Bachelor’s degree in science/engineering

Outils

BigQuery

GCS

Dataproc

AWS (S3, EMR)

GCP

Spark SQL

Hive

Trino

Azkaban

Airflow

Databricks

Description du poste

Wonder is seeking a Staff Data Engineer to provide technical leadership across core data systems. You will own the architecture of multiple pipelines and data products, mentor engineers, and set standards for data modeling, testing, observability, and cost efficiency.

This is a hands‑on leadership role guiding teams toward scalable, reliable data solutions. New York and Chicago offices offer opportunities to collaborate with product, analytics, and platform teams while delivering trusted