Data Engineer
@ Crossing Hurdles

Hybrid
$100,000
Hybrid
Full Time
Posted 24 days ago

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XXXXXXXXX XXXXXXXXX XXXXXXXXX****** @crossinghurdles.com
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Job Details

Overview

Crossing Hurdles is a recruitment firm referring top candidates to leading AI research labs. The Data Engineer role is full-time and remote with compensation up to 100,000 USD/year.

Role Responsibilities

  • Build robust data pipelines from diverse sources including MongoDB, Airtable, PostHog, and production databases.
  • Design dbt models and transformations to unify data tables into clean schemas.
  • Implement scalable, fault-tolerant workflows using Fivetran, dbt, SQL, and Python.
  • Collaborate with engineers, data scientists, and business stakeholders.
  • Ensure data quality, reliability, and continuous pipeline performance improvement.

Requirements

  • Proven experience in data engineering with strong proficiency in SQL and Python.
  • Experience with modern data tools like Fivetran, dbt, Snowflake, or similar platforms.
  • Skilled in building and managing large-scale ETL/ELT pipelines.
  • Strong understanding of data modeling, schema design, and transformation best practices.
  • Familiarity with data governance, monitoring, and quality assurance processes.
  • Bonus: Experience supporting machine learning workflows or analytics platforms.
  • Must have access to a desktop or laptop (Chromebooks not supported).

Application Process

Submit your resume highlighting relevant data engineering experience. Selected candidates will be invited to interview and onboarding sessions. Compensation and role details will be shared during the process.

Key skills/competency

Data Pipelines, SQL, Python, Fivetran, dbt, ETL, Data Modeling, Snowflake, Data Quality, Collaboration

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How to Get Hired at Crossing Hurdles

🎯 Tips for Getting Hired

  • Tailor your resume: Highlight data pipeline and ETL expertise.
  • Showcase project experience: Emphasize SQL and Python skills.
  • Research Crossing Hurdles: Understand their recruitment approach.
  • Prepare for technical questions: Practice data modeling and transformation queries.

📝 Interview Preparation Advice

Technical Preparation

Practice SQL queries and data transformations.
Review Python coding and debugging techniques.
Study modern ETL tools and pipeline construction.
Familiarize with dbt and Fivetran usage.

Behavioral Questions

Describe team collaboration experiences.
Explain conflict resolution with stakeholders.
Detail a time when you improved processes.
Discuss adapting to new technology quickly.

Frequently Asked Questions