Senior Data Engineer - Remote, Build Scalable Pipelines

Midnite; United States; À distance; USD 113 000 - 133 000; Plein temps

Avantages offerts par ce poste

Private health insurance

Income protection

Holiday entitlement increase with long

Home office setup support

Nursery salary sacrifice

Tech and holiday salary sacrifice

Retail discounts

Team socials

Résumé du poste

Midnite is a next-generation sports betting and gaming platform focused on delivering modern, intuitive experiences. We are a high-performance team with strong ownership, shipping rapidly and iterating on data platforms to enable fast analytics and decision making.

The Senior Data Engineer will own critical data pipelines, work with modern data tooling, and help shape how data engineering is done as the team scales.

Qualifications

• Extensive production-grade data engineering experience.
• Strong Python and SQL proficiency in real data environments.
• Experience with modern data tooling (Snowflake, dbt, Dagster, Airflow, AWS).
• Knowledge of data modelling principles and pragmatic application.
• Focus on testing, monitoring, alerting and data quality.

Responsabilités

• Design, build and maintain scalable data pipelines from ingestion to analytics enablement.
• Own end-to-end data engineering projects and develop reliable SQL-based data models.
• Improve staging, testing, monitoring and data quality across pipelines.
• Collaborate with Product, Analytics, Engineering and business stakeholders.
• Participate in code reviews and raise engineering standards across the team.

Connaissances

Python

SQL

Snowflake

Dagster

dbt

AWS

Data modelling

Testing

Monitoring

Data quality

Outils

Airflow

Snowflake

dbt

Dagster

AWS

Description du poste

Midnite is a next-generation sports betting and gaming platform focused on delivering modern, intuitive experiences. We are a high-performance team with strong ownership, shipping rapidly and iterating on data platforms to enable fast analytics and decision making.

The Senior Data Engineer will own critical data pipelines, work with modern data tooling, and help shape how data engineering is done as the team scales.