Hybrid Data Engineer, Foundations & Big Data Pipelines

Superhuman Labs, Inc.; San Francisco (CA); Hybrid; USD 175,000 - 245,000; Full time

Benefits offered by this job

Hybrid work model

Health, dental, vision benefits

401(k) matching

Paid parental leave

Job summary

Superhuman Labs, Inc. seeks a Data Engineer to join the Data Foundations team, building robust, scalable data pipelines and data lakes to process billions of daily events. You will shape architecture and contribute to production-grade data infrastructure across product surfaces.

The role blends data engineering, data-intensive applications, and data modeling, with ownership from strategy to production. Hybrid work is offered with preferred SF or Seattle locations.

Qualifications

• 3+ years of experience running live production environments, including high-load or data-intensive workflows, with a focus on uptime and reliability.
• Proficient in SQL and Python, with deep hands-on experience in Spark and a modern lakehouse or cloud data warehouse (Databricks, Delta Lake, dbt, Snowflake, or similar).
• Strong knowledge of ETL/ELT design patterns, orchestration tools (Airflow, dbt, or Dagster), data quality frameworks, and CI/CD for data with Git-based deployments.
• Data modeling and data warehouse design skills, along with a rigorous approach to data quality and observability.
• Hands-on experience with modern data storage technologies (Delta Lake, Snowflake, BigQuery, or Redshift).
• Clear communication and collaboration across diverse teams turning business needs into robust data solutions and trustworthy metrics.
• Strong ownership mindset, end-to-end responsibility for systems from strategy to production and reliability.
• Strong acumen for scalable, complex data processing and prioritization across multiple projects in a fast-paced environment.

Responsibilities

• Design and implement robust, scalable data pipelines and systems for large data volumes.
• Build large-scale data pipelines and data lakes (Spark/Databricks) ingesting billions of daily events.
• Design solutions to keep data available, secure, and scalable for real-time and batch processing.
• Own data quality, freshness, and reliability for foundational datasets with automated checks and alerts.
• Build ETL frameworks and tooling for other data teams and data scientists to self-serve datasets.
• Collaborate with product teams, back-end engineers, ML engineers, and data science to turn business questions into data products.
• Partner with leadership to shape the team’s charter and technical roadmap.

Skills

SQL

Python

Spark

Databricks

Delta Lake

dbt

Snowflake

Airflow

Dagster

Git

Tools

Airflow

dbt

Dagster

Git

Job description

Superhuman Labs, Inc. seeks a Data Engineer to join the Data Foundations team, building robust, scalable data pipelines and data lakes to process billions of daily events. You will shape architecture and contribute to production-grade data infrastructure across product surfaces.

The role blends data engineering, data-intensive applications, and data modeling, with ownership from strategy to production. Hybrid work is offered with preferred SF or Seattle locations.