Senior Data Engineer

This position is a senior engineering role at a data and AI company - which means you'll be close to the product, close to customers, and building systems that are used from day one.

You'll design and ship the data infrastructure at the core of what we sell: modern data platforms, scalable pipelines, and the reporting layers our clients run their businesses on. This role is client facing - you'll be in the room with stakeholders, translating business problems into architecture, and owning the results.

You'll work directly with the CEO and alongside a small, senior team. The problems are real, the feedback loop is short, and the surface area is large. Expect to move fast and own a lot. This is a fully remote position, with the expectation that you’ll work primarily Eastern Time hours to stay closely aligned with our team and clients.

What You'll Build

Modern data platforms You'll architect and implement data platforms end-to-end. You have deep familiarity with modern data architecture - lakehouse vs. warehouse tradeoffs, ELT patterns, semantic layers, orchestration - and you've implemented Snowflake, BigQuery, or Databricks in production. You know when to use what, and why.

Scalable, secure pipelines You'll build ingestion and transformation pipelines that hold up under real conditions. You have hands-on knowledge of how to build pipelines that scale with data volume and stay secure - access controls, data governance, encryption, and auditability are part of your design, not an afterthought.

Data models that last You're opinionated about data modeling. You've worked with star schema, Data Vault, OBT, etc. and you can argue for the right approach given the business context. You design models for business, analytics and AI consumption.

Streaming and real-time systems You've implemented streaming pipelines in production, and are familiar with popular technologies such as Kafka, Flink, Redpanda, or similar. You understand the operational realities of streaming: schema evolution, backpressure, exactly-once semantics, and when batch is actually the right answer.

Client-facing delivery You'll work directly with client teams - scoping requirements, presenting architecture decisions, and walking stakeholders through tradeoffs. You communicate clearly with both engineers and business leaders, and you're oriented toward results, not just technically elegant solutions.

What You Bring

• Significant experience building production data systems, with senior-level ownership of architecture decisions.
• Deep understanding of modern data architecture and platforms - you've implemented Snowflake, BigQuery, or Databricks, not just used them.
• Hands-on knowledge of building scalable and secure data pipelines: orchestration, transformation frameworks (dbt or similar), cloud infrastructure (AWS or GCP).
• Strong opinions on data modeling best practices - Kimball, star schema, Data Vault - and the judgment to pick the right one for the problem.
• Experience implementing streaming pipelines with Kafka, Flink, Redpanda, or similar.
• Clear communication. This role is client facing - you'll present to business stakeholders, explain tradeoffs in plain language, and build trust through delivery.
• A business orientation and focus on results: you understand that the pipeline exists to answer a business question, and you make tradeoffs accordingly.
• A bias for doing: you'll write the query, sketch the schema, or spin up the prototype if that's what moves things forward.

Why This Role

You'll be a senior engineer at a venture-backed company working on one of the most consequential problems in business right now: making company data actually usable.

Most engineers spend years building inside someone else's platform. Here, you'll help define what the platform is - and your scope and impact will grow as the company does.