Growth Data Engineer - Scalable Pipelines & ML Data

Zoomcar; San Francisco (CA); Hybrid; USD 190,000 - 240,000; Full time

Benefits offered by this job

Health care

Disability & life insurance

401(k) matching

Paid parental leave

Paid time off

Holidays

Floating holidays

Flexible sick time

Stipends

Professional development budget

Job summary

Superhuman is hiring a Data Engineer on the RTM Growth team to own pipelines, models, and datasets powering user acquisition and growth across our AI-native productivity platform. You will partner with Growth, Performance Marketing, and Data Science to turn signals into reliable data.

This high-ownership role combines data engineering, machine learning, and growth. You will build scalable, well-documented data products, ensure data quality, and continuously improve the data platform as we scale.

Qualifications

• 3+ years of experience building and operating production data pipelines and data platforms, ideally for growth, marketing, or experimentation use cases.
• You’re highly 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).
• You’ve supported machine learning workflows end-to-end, building feature pipelines, serving training and inference datasets, and partnering with data scientists to move models into production.
• You have strong data-modeling and warehouse-design skills and a rigorous approach to data quality and observability.
• You have experience with workflow orchestration and CI/CD for data (for example, Databricks Workflows or Airflow, with Git-based deployment).
• You’re comfortable using AI-assisted development tools like Claude Code or Codex to move faster, and you have the judgment to validate and supervise their output.
• You communicate clearly and collaborate well with partners across Growth, Marketing, and Data Science.
• You care about business impact and enjoy turning ambiguous growth questions into reliable, scalable data products.
• You’re a self-starting problem-solver who thinks from first principles, manages priorities across multiple projects, and thrives in a fast-paced, results-driven environment.

Responsibilities

• Design, build, and own scalable data pipelines (Spark/Databricks) that power ad bidding and paid acquisition optimization across channels such as Google, Meta, and LinkedIn.
• Build and maintain the feature and training datasets that machine learning models rely on for bid optimization, budget allocation, and audience targeting, and help productionize those models alongside Data Science.
• Develop the measurement, attribution, and experimentation data layer behind web and landing-page optimization, so Growth can trust the numbers behind every test.
• Model growth and marketing data into clean, well-documented, reusable tables that analysts and data scientists can self-serve from.
• Own data quality, freshness, and reliability for growth-critical datasets, with automated checks, monitoring, and alerting.
• Partner with Growth, Marketing, Analytics Engineering, and Data Science to translate business questions into robust data models and trustworthy metrics.
• Continuously improve the performance, cost efficiency, and developer experience of our growth data platform.

Skills

SQL

Python

Spark

Data Modeling

Data Quality

Observability

CI/CD for Data

Communication

Problem Solving

Tools

Databricks

Delta Lake

dbt

Snowflake

Airflow

Git

Databricks Workflows

Job description

Superhuman is hiring a Data Engineer on the RTM Growth team to own pipelines, models, and datasets powering user acquisition and growth across our AI-native productivity platform. You will partner with Growth, Performance Marketing, and Data Science to turn signals into reliable data.

This high-ownership role combines data engineering, machine learning, and growth. You will build scalable, well-documented data products, ensure data quality, and continuously improve the data platform as we scale.