Senior Data Engineer: End-to-End Data Pipelines & Analytics

Hitmarker | Gaming Jobs; San Francisco (CA); On-site; USD 221,000 - 245,000; Full time

Job summary

Discord is seeking a Senior Data Engineer to own end-to-end data models and pipelines that power analytics, experimentation, and dashboards. You will partner with data science, ML, and engineering teams to improve instrumentation, data quality, and cost efficiency across large-scale datasets.

You’ll design architectures for massive data, mentor engineers, and drive adoption of your work through documentation and collaboration. A strong foundation in SQL, Python, and data modeling is essential.

Qualifications

• 4+ years of experience building and operating production data pipelines with high volumes of consumer data.
• Nice-to-have experience with large-scale data platforms.
• Experience implementing robust data quality checks across datasets.

Responsibilities

• Own the data models and pipelines for a functional area end to end, from design through implementation and adoption.
• Build and maintain foundational datasets powering analytics, modeling, experimentation, and dashboards/reports.
• Design data architectures for massive, complex data balancing usability, performance, and cost.
• Partner with data science, ML, and engineering teams to improve instrumentation.
• Build data quality audits at scale with alerting and anomaly detection.
• Find and act on opportunities to improve pipeline and dashboard performance and cost.
• Drive adoption of your work through documentation and enablement.

Skills

Data modeling

SQL

Python

Data quality checks

Communication

Stakeholder management

Ambiguity handling

Team collaboration

Tools

BigQuery

Airflow

dbt

Looker

Tableau

Job description

Discord is seeking a Senior Data Engineer to own end-to-end data models and pipelines that power analytics, experimentation, and dashboards. You will partner with data science, ML, and engineering teams to improve instrumentation, data quality, and cost efficiency across large-scale datasets.

You’ll design architectures for massive data, mentor engineers, and drive adoption of your work through documentation and collaboration. A strong foundation in SQL, Python, and data modeling is essential.