Data Engineer, Data Products

The role

You will own complex consumer-data domains and turn raw signals into trusted attributes and production data products. You will investigate datasets, design domain models, and build ingestion and transformation pipelines to power applications, agents, and APIs.

What you will do

• Own one or more complex consumer-data domains end-to-end.
• Investigate large, messy and unfamiliar datasets.
• Design and build durable domain models, derived attributes and entity relationships.
• Build and operate ingestion and transformation pipelines.
• Identify and evaluate new data sources.
• Make data outputs trustworthy enough to be consumed autonomously.
• Partner with data scientists, platform engineers, product engineers and customer-facing teams.
• Use LLMs, embeddings and modern AI development tools to improve engineering velocity.
• Find new ways to create and protect business value through proprietary data assets.

Required qualifications

• 2-5+ years working as a data engineer, software engineer or applied data scientist in a data-heavy context.
• Highly proficient in Python and SQL.
• Driven by first-principles thinking.
• Strong intuition for data cleaning, ingestion and data modeling.
• Comfortable building and deploying production data pipelines.
• Able to balance analytical depth with engineering pragmatism.
• Comfortable owning an ambiguous initiative end-to-end in a lean, fast-changing environment.
• Willingness to work in our New York City office.

Nice to have

• Experience working with large, messy, multi-source datasets where the semantics were not obvious and documentation was incomplete.
• Experience with consumer data, identity resolution, entity graphs, property data, behavioral or intent data, or other complex third-party data domains.
• Experience with orchestration tools such as Dagster, Airflow or Prefect and transformation tools such as dbt or SQLMesh.
• Experience with analytical databases such as Snowflake, Redshift or BigQuery and familiarity with transactional databases such as Postgres or MySQL.
• Experience with lakehouse or distributed-processing systems such as Spark, Iceberg, Trino or AWS Glue.
• Familiarity with AWS or another major cloud platform.
• Exposure to ML eng/ops, applied ML or feature engineering.
• Effective use of AI coding tools such as Claude Code, Cursor or OpenCode as a force multiplier.
• Prior experience at an early-stage startup.

Benefits

• Relocation package.
• Competitive equity.
• Medical.
• Dental.
• Vision.

Before you apply

• We test rigorously for data problem solving skills in our interview process.

About the company

Minerva builds AI for marketing leaders, working with marketers to automate and accelerate workflows with AI agents. The company has raised $20M from various investors.