Senior Data Platform Engineer

super; United States; On-site; USD 110,000 - 140,000; Full time

Benefits offered by this job

Medical / Health Insurance

Open Annual Leave

Employee Assistance Programme

Training & Learning Development

Job summary

Super is seeking a senior data engineer to design, build, and scale ETL/ELT pipelines powering self-service analytics for a global platform. You will own end-to-end data initiatives, model analytics-ready data, and maintain curated data layers and semantic models.

You will partner with software engineers, analysts, product managers, and stakeholders to translate ambiguous requirements into robust data solutions. Expect a collaborative, fast-paced environment.

Qualifications

• Strong SQL and Python skills with production data pipelines.
• Deep understanding of dimensional modeling and data warehouse design.
• Experience owning projects end-to-end with multiple stakeholders.

Responsibilities

• Design, build, and evolve scalable ETL/ELT pipelines for high‑volume data.
• Own medium‑to‑large data initiatives end-to-end from design to production.
• Model reliable analytics-ready data using warehouse methodologies.
• Develop curated analytical layers, semantic models, and data marts for self-service analytics.
• Orchestrate workflows with Airflow for reliability and observability.
• Collaborate with engineers, analysts, PMs, and business to translate requirements.
• Identify and drive improvements in data quality and performance.
• Contribute to architecture and engineering decisions and mentor junior engineers.

Skills

SQL

Python

Data modeling

DW design

Tools

Apache Airflow

Dagster

Snowflake

BigQuery

Job description

Super is seeking a senior data engineer to design, build, and scale ETL/ELT pipelines powering self-service analytics for a global platform. You will own end-to-end data initiatives, model analytics-ready data, and maintain curated data layers and semantic models.

You will partner with software engineers, analysts, product managers, and stakeholders to translate ambiguous requirements into robust data solutions. Expect a collaborative, fast-paced environment.