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About the Role

Minerva's data is a core product, and this role involves taking ownership of complex consumer-data domains. You will develop a deep understanding of datasets, transform raw signals into trusted attributes, and create production data products. This unique position allows for immediate revenue generation from your work output within weeks.

Responsibilities

• Own one or more complex consumer-data domains end-to-end, becoming the person responsible for both understanding the data and advancing the products built from it.
• Investigate large, messy and unfamiliar datasets. Establish their grain, keys, relationships, coverage, failure modes and fitness for different product use cases.
• Design and build durable domain models, derived attributes and entity relationships that can power Minerva's applications, AI agents, APIs, customer deliveries and predictive models.
• Build and operate the ingestion and transformation pipelines required to bring your work into production, including validation, observability, backfills and recovery.
• Go on data quests: identify and evaluate new sources, determine how they can improve our consumer graph and find clever ways to extract signal from imperfect inputs.
• Make data outputs trustworthy enough to be consumed autonomously. Define quality checks, provenance and guardrails that distinguish reliable signal from convenient but misleading data.
• Partner with data scientists, platform engineers, product engineers and customer-facing teams to turn open-ended business or product questions into scalable data products.
• Use LLMs, embeddings and modern AI development tools where they materially improve data standardization, classification, enrichment or engineering velocity.
• Find new ways to create and protect business value through Minerva's proprietary data asset, from improving existing products to opening entirely new revenue opportunities.

Requirements

• 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. You can take an ambiguous data problem, determine what must be true, interrogate the available evidence and design a practical path to an answer.
• Strong intuition for data cleaning, ingestion and data modeling.
• Comfortable building and deploying production data pipelines, not just analyzing data in notebooks or handing specifications to another engineering team.
• 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.
• Eagerness to learn, grow and raise the bar with your coworkers.

Skills

• Python
• SQL
• Data cleaning
• Data ingestion
• Data modeling
• Building and deploying production data pipelines
• LLMs
• Embeddings
• Modern AI development tools
• Consumer data
• Identity resolution
• Entity graphs
• Property data
• Behavioral or intent data
• Orchestration tools (e.g., Dagster, Airflow, Prefect)
• Transformation tools (e.g., dbt, SQLMesh)
• Analytical databases (e.g., Snowflake, Redshift, BigQuery)
• Transactional databases (e.g., Postgres, MySQL)
• Lakehouse or distributed-processing systems (e.g., Spark, Iceberg, Trino, AWS Glue)
• AWS or another major cloud platform
• ML eng/ops
• Applied ML
• Feature engineering
• AI coding tools (e.g., Claude Code, Cursor, OpenCode)

Location

• New York City

Work Type

• Full time
• On-site

Experience Level

• 2-5+ years

Salary/Compensations

• $200,000 to $225,000

Benefits

• Competitive equity
• Marquee benefits package
• Relocation package

About the Company

• Minerva builds AI for marketing leaders. Our platform lets marketers focus on telling the story of their brand while AI agents handle the operationally intensive work: data management, analytics, campaign generation, measurement and reporting.
• Everything is built on Minerva's proprietary consumer graph: an identity and attribute layer covering 270M+ U.S. consumers across 1,000+ through-time attributes. On top of it sit two agentic systems built in partnership with OpenAI: an Agentic Data Engineer that unifies and standardizes a brand's first-party data in hours, and an Agentic Data Scientist that trains robust targeting models at scale.
• Together, our data and platform improve the quality of a brand's first-party data, lift campaign performance and give marketing teams their time back.
• Our data team built Minerva's initial data product in less than a year and has already become best-in-class within the consumer data ecosystem.
• We work with leading consumer brands across categories, including the NBA, Capital One, Hard Rock Stadium Group / Miami Dolphins, Wander and Trust & Will.
• We've raised $20M from The General Partnership, 8VC, Lingotto, NBA Investments, Topology Ventures, Future Positive, Background Capital and many others.
• Our team brings together operators and investors from Citadel, Dentsu, Bridgewater, Meta Superintelligence and Lazard, alongside researchers from Berkeley, MIT, Stanford and Cambridge.