Data Engineer

@ Crossing Hurdles

About the Data Engineer Role

At Crossing Hurdles, we work as a referral partner, referring candidates to our partner who collaborates with world-leading AI research labs to build and train cutting-edge AI models.

Responsibilities

The Data Engineer will:

• Build robust data pipelines to ingest, transform, and consolidate data from diverse sources including MongoDB, Airtable, PostHog, and production databases.
• Design dbt models and transformations to unify disparate data tables into clean, production-ready schemas.
• Implement scalable, fault-tolerant workflows using Fivetran, dbt, SQL, and Python.
• Collaborate with engineers, data scientists, and business stakeholders to ensure data availability, accuracy, and usability.
• Own data quality and reliability across the entire data stack from ingestion to consumption.
• Continuously improve pipeline performance, monitoring, and scalability.

Requirements

Candidates must have proven experience in data engineering with strong proficiency in SQL and Python, familiarity with modern data stack tools like Fivetran, dbt, and Snowflake, and experience in building and maintaining large-scale ETL/ELT pipelines. A strong understanding of data modeling, schema design, and transformation best practices is required. Experience with data governance, monitoring, and quality assurance is a plus. Bonus points for prior experience with machine learning workflows or analytics platforms. Candidates must have access to a desktop or laptop (Chromebooks are not supported).

Application Process

The application process is 15 minutes long and includes:

• Resume upload
• Participation in a 10 minute AI interview
• Submission of a form

Key skills/competency

• SQL
• Python
• ETL
• Data Pipelines
• dbt
• Fivetran
• Data Modeling
• Data Quality
• Collaboration
• Scalability