Data Platform Engineer

This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Develop the Owner's data platform, which serves as the foundation for analytics, AI, and decision-making across the organization.

• Architect and construct data systems tailored for analytics, AI, and business intelligence applications.

• Transition individualized custom scripts into replicable, production-ready pipelines.

• Assume ownership and enhance Snowflake, dbt, Dagster, ingestion, and reverse ETL platforms.

• Elevate data reliability, consistency, and compliance standards.

• Create self-service tools for analysts and partners.

• Pinpoint and implement cost and performance optimizations across computing, storage, and processing resources.

• Lead technical decisions and establish best practices for data ingestion, transformation, orchestration, and storage.

• Offer code reviews and technical mentorship to colleagues.

• Contribute to the development of a robust data platform team.

• Collaborate with data platform engineers, analysts, product engineers, business teams, and leadership in Product and Engineering.

• Transition internal BI infrastructure from Hex to dbt, ensuring it is reproducible, production-ready, and self-service.

• Possibly concentrate on core pipeline/platform infrastructure or on the semantic layer bridging LLMs and data.

⛳️ Requirements

• Over 5 years of experience in data engineering or analytics engineering.

• Proficient in SQL and Python.

• Practical production experience with Snowflake.

• Solid foundational knowledge of ETL/ELT processes, including dbt and a modern orchestrator like Dagster or Airflow.

• Demonstrated success in impact-driven problem-solving within fast-paced settings, emphasizing high-quality, dependable, and efficient systems.

• Strong technical communication abilities, with a history of collaboration among technical and non-technical stakeholders.

• Comfortable starting from scratch, possessing strong opinions and the capability to establish structure where it's lacking.

• A proactive sense of ownership, curiosity, and dedication to ongoing learning.

• Must be currently and permanently located in the United States or Canada.

• Disclosure of visa sponsorship status is necessary.

• Experience in developing a semantic layer or data infrastructure for AI/ML and LLM retrieval (RAG, feature stores, dataset compliance) is a plus.

• Familiarity with reverse ETL or personalization platforms is a bonus.

• Experience with Databricks is an advantage.

• Knowledge of data governance, access control, and cost optimization for large-scale data platforms is beneficial.

• Experience in mentoring engineers and promoting a culture of learning and technical excellence is an asset.

• A genuine interest in the product and its customers is a plus.

🏝️ Benefits

• Competitive pre-IPO equity package.

• Comprehensive health benefits.

• Flexibility to work from anywhere (remote-first environment).

• Unlimited paid time off (PTO).

• Additional fun perks.