Senior Data Engineer - Paradox Machines
Senior, client-facing data engineer at a small venture-backed data & AI company: you design and ship the data platforms, scalable/secure pipelines, data models, and streaming systems the company sells, working directly with the CEO and clients. Core stack: Snowflake/BigQuery/Databricks, dbt, Kafka/Flink, AWS/GCP.
- Compensation
- $140K–$160K / yr
- Location
- United States
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Significant experience building production data systems with senior-level ownership of architecture decisions
- Deep understanding of modern data architecture (lakehouse vs warehouse, ELT, semantic layers, orchestration)
- Implemented Snowflake, BigQuery, or Databricks in production
- Hands-on experience building scalable and secure data pipelines (orchestration, transformation frameworks like dbt)
- Cloud infrastructure experience (AWS or GCP)
- Strong data modeling knowledge (Kimball, star schema, Data Vault, OBT) and judgment to pick the right approach
- Experience implementing streaming pipelines (Kafka, Flink, Redpanda, or similar)
- Clear communication with engineers and business stakeholders; comfort presenting architecture decisions to clients
- Business orientation and focus on results
- Bias for doing: writing queries, sketching schemas, spinning up prototypes
Full description
The Opportunity
This 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 and AI layers our clients run their businesses on. Increasingly, the consumers of our platforms aren't just dashboards and analysts - they're apps, agents, and people who expect to ask questions in natural language and get correct answers. Building data systems that serve that expectation well is a core part of this job.
This role is client facing - you'll be leading customer projects, implementing solutions, and act as their trusted partner. You'll work directly with the CEO and alongside a growing, 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.
What You'll BuildModern data platforms You'll architect and implement data platforms end-to-end. You have deep familiarity with modern data architecture - warehouse vs. data lake, table formats, ELT patterns, semantic layers, orchestration - and you've implemented Snowflake, BigQuery, or Databricks in production. You know when to use what, and why. Our customers will look to you for recommendations - you should have an equally strong understanding of both first principles data engineering and modern tooling.
Data models built for new consumption patterns 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 the right answer. You understand that with agentic consumption, the need for “near real time” data is more prevalent than ever.
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
- Clear communication. This role is client facing - you'll present to business stakeholders, explain tradeoffs in plain language, and build trust through delivery. This is the most important part of the job.
- Significant experience building production data systems, with senior-level ownership of architecture decisions.