Senior Data Platform Engineer & Tech Lead

Mozilla; New York (NY); Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Health and dental plan

Mental health support

Paid time off (vacation & sick)

Parental leave

401(k) / RRSP retirement plan

Learning and professional development

Life/AD&D and disability insurance

Wellbeing stipend

Employee referral bonus

Internet reimbursement for remote

Office budget for remote setup

Job summary

Mozilla’s Data Engineering team is seeking a Senior Staff Data Engineer / Data Platform Engineer to help advance our Data Platform infrastructure. The role blends hands-on engineering with technical leadership across Data Platform Engineering and Data Engineering, in a hybrid work model.

You will design and implement scalable data systems handling tens of terabytes per day, mentor engineers, and collaborate with Data Science, Product, Legal, and Policy teams to drive data products and governance.

Qualifications

• 10+ years of combined experience in Data Engineering, Data Platform Engineering, Data Science, or Data Analyst roles.

Responsibilities

• Design, build, and improve data infrastructure at scale (tens of terabytes per day).
• Drive cross-functional projects with stakeholders across Mozilla, including Data Science, Product, Legal, Policy, and Engineering.
• Mentor teammates and develop engineering best practices across the Data Organization.
• Work with Data Science to design and implement useful data abstractions.

Skills

Software engineering fundamentals

Modularity

Abstraction

Data structures

Algorithms

Mentoring

Leadership

SQL

Python

Cloud platforms

Tools

Looker

Fivetran

Kubernetes / GKE

Airflow / Cloud Composer

Terraform

Pub/Sub

BigQuery

Dataflow (Apache Beam)

Job description

Mozilla’s Data Engineering team is seeking a Senior Staff Data Engineer / Data Platform Engineer to help advance our Data Platform infrastructure. The role blends hands-on engineering with technical leadership across Data Platform Engineering and Data Engineering, in a hybrid work model.

You will design and implement scalable data systems handling tens of terabytes per day, mentor engineers, and collaborate with Data Science, Product, Legal, and Policy teams to drive data products and governance.