Senior Analytics Engineer

About the role

Confido is the AI infrastructure powering modern CPG — the platform that 200+ brands like OLIPOP, Simple Mills, Dr. Squatch, and Tropicana use to run everything from deductions to production planning. Finance, accounting, sales, and operations, unified in one system for the first time.

We're growing 5x year over year and recently raised a $15M Series A led by Footwork and Y Combinator. We're a small, in-person team in New York City, which means the people who join now shape the product, the culture, and the company itself.

If you want your work on shelves everywhere — and outsized ownership while you build — we'd love to meet you.

The Role

At Confido, data powers everything from customer-facing insights to internal decision making. We are looking for an Analytics / Data Engineer to build the foundation that enables scalable reporting, trusted metrics, and seamless data access across the company.

What You'll Do

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Design, build, and maintain our centralized data warehouse and analytics infrastructure.

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Develop scalable data models that power reporting, dashboards, operational workflows, and customer-facing data exports.

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Serve as the steward of Confido's data landscape, creating visibility into data ownership, lineage, and dependencies while ensuring data is discoverable, trustworthy, and easy to consume across the organization.

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Consolidate and standardize data models across multiple products and teams, creating a single source of truth for the business.

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Establish data engineering best practices, including data modeling standards, testing, documentation, monitoring, and governance.

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Partner closely with Engineering, Product, Operations, and Customer teams to define metrics and deliver actionable insights.

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Improve data quality, reliability, and accessibility across the organization.

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Enable self-service analytics by creating scalable datasets and semantic layers for downstream consumers.

What We're Looking For

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4-8 YOE building and operating modern data warehouses and analytics platforms.

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Strong SQL skills and experience modeling large datasets.

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Deep experience with distributed data processing, including designing performant ETL pipelines and optimizing large-scale data workloads.

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Experience with data pipeline orchestration, ETL/ELT workflows, and data infrastructure.

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Familiarity with modern analytics tooling such as Snowflake, dbt, or similar technologies.

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Ability to balance immediate business needs with long-term platform investments.

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Excellent communication skills and a track record of working cross-functionally with technical and non-technical stakeholders.